Computational and Systems Biology 2020 Books Catalogue

Computational &

Systems Biology

www.cambridge.org/csb

2020

CONTENTS Textbooks Computational Biology Computational Neurobiology Genomics Systems Biology Phylogenetics Biostatistics Cambridge Series in Statistical and Probabilistic Mathematics Institute of Mathematical Statistics Textbooks Epidemiology Data Science & Machine Learning Programming Of related interest

This catalogue contains a selection of our most recent publishing in this area. Please visit our website for a full and searchable listing of all our titles in print and also an extensive range of news, features and resources. Our online ordering service is secure and easy to use.

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Textbooks

3

HIGHLIGHT TEXTBOOK

Modern Statistics for Modern Biology Susan Holmes Stanford University, California

and Wolfgang Huber European Molecular Biology Laboratory

Designed for a new generation of biologists, this textbook teaches modern computational statistics by using R/Bioconductor to analyze experimental data from high-throughput technologies. The presentation minimizes mathematical notation and emphasizes inductive understanding from well-chosen examples, hands-on simulation, and visualization.

‘This is a gorgeous book, both visually and intellectually, superbly suited for anyone who wants to learn the nuts and bolts of modern computational biology.

It can also be a practical, hands-on starting point for life scientists and students who want to break out of ‘canned packages’ into the more versatile world of R coding. Much richer than the typical statistics textbook, it covers a wide range of topics in machine learning and image processing. The chapter on making high-quality graphics is alone worth the price of the book.’

William H. Press, University of Texas, Austin ‘The book is a timely, comprehensive and practical reference for anyone working with modern quantitative biotechnologies. It can be read at multiple levels. For scientists with a statistics background, it is a thorough review of key methods for design and analysis of high-throughput experiments. For life scientists with a limited exposure to statistics, it offers a series of examples with relevant data and R code. Avoiding buzzwords and hype, the book advocates appropriate statistical practice for reproducible research. I expect it to be as influential for the life sciences community as Modern Applied Statistics with S, by Venables and Ripley or Introduction to Statistical Learning, by James, Witten, Hastie and Tibshirani are for applied statistics.’

Olga Vitek, Northeastern University, Boston 2019 276 x 216 mm 402pp 978-1-108-70529-5 Paperback £49.99 / US$64.99 For all formats available, see

www.cambridge.org/9781108705295

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4

Textbooks

TEXTBOOK

Quantitative Genetics Armando Caballero Universidade de Vigo, Spain

This accessible and up-to-date text uses applied examples and model problems to enhance students’ understanding of the concepts and applications of quantitative genetics. It provides the most current and in-depth view of the field for researchers and professionals in genetics, genomics, plant and animal breeding, and conservation science.

‘Quantitative genetics as a scientific discipline isn’t dead just yet, despite predictions of its demise over many decades. In fact, it is very much alive in the genomics era, across a wide range of disciplines, including plant and animal breeding, evolutionary genetics and human (medical) genetics. Armando Caballero’s timely textbook, a translation and update from his Spanish version, combines a description of the theory and methods underlying quantitative trait variation in populations with data examples and applications from modern genome technologies. It is an excellent introduction to the field, and demonstrates once again how population and quantitative genetics theory has stood the test of time and is highly relevant today.’

Peter M. Visscher, University of Queensland ‘Armando Caballero’s work is a masterful tour through both evolutionary and applied quantitative genetics. It provides a fruitful and unusual blend of population and quantitative genetics, and it will be extremely useful for anyone who wants to learn more about either of these fields.’

Michael Whitlock, University of British Columbia 2020 244 x 170 mm 338pp 101 b/w illus. 43 tables 978-1-108-48141-0 Hardback £74.99 / US$99.99 978-1-108-72235-3 Paperback £29.99 / US$38.99 For all formats available, see

www.cambridge.org/9781108481410

Textbooks

TEXTBOOK

TEXTBOOK

Cellular Biophysics and Modeling

Analyzing Network Data in Biology and Medicine

A Primer on the Computational Biology of Excitable Cells

5

An Interdisciplinary Textbook for Biological, Medical and Computational Scientists

Greg Conradi Smith College of William and Mary, Virginia

An integrated guide to cellular biophysics and nonlinear dynamics, introducing students to the mathematical modeling of excitable cells. It combines empirical physiology and mathematical theory to present key interdisciplinary tools, highlighting how quantitative approaches can complement and advance bench research.

Contents: Part I. Models and Odes; Part II. Passive Membranes; Part III. Voltage-Gated Currents; Part IV. Excitability and Phase Planes; Part V. Oscillations and Bursting.

‘In this text, Conradi Smith does an excellent job of teaching students with no mathematical training beyond calculus how to use differential equations to understand the basic principles of cell physiology and excitability. He skilfully walks students through the steps of modeling and analysis, all the while working to develop intuition and insight into how things work.

His emphasis on computational methods for solution as well as graphical and geometrical means for interpretation enables him to communicate complex ideas in understandable ways. Furthermore, his patience and attention to detail will be appreciated by those students who have not had extensive exposure to the art of mathematical modeling. This text is a wonderful addition to the mathematical biology textbook literature.’

James P. Keener, University of Utah

Edited by Nataša Pržulj University College London and Barcelona Supercomputing Center

Bringing together leading experts in the field of network data analysis, this text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning. Using real-world biological and medical examples, applications of these theories are discussed and creative thinking is encouraged in the analysis of such complex network data sets.

2019 247 x 174 mm 643pp 196 b/w illus. 42 tables 978-1-108-43223-8 Paperback £39.99 / US$49.99 For all formats available, see

www.cambridge.org/9781108432238

2019 247 x 174 mm 394pp 21 b/w illus. 248 colour illus. 6 tables 978-1-107-00536-5 Hardback £94.99 / US$125.00 978-0-521-18305-5 Paperback £38.99 / US$49.99 For all formats available, see

www.cambridge.org/9781107005365

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Computational Biology Integer Linear Programming in Computational and Systems Biology An Entry-Level Text and Course

Dan Gusfield University of California, Davis

Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.

Contents: Part I; Part II. ‘In his classic accessible teaching style, Gusfield teaches us why integer linear programming (ILP) is the most useful mathematical idea you’ve probably never heard of. Read this book to learn how what you don’t know can hurt you, and why ILP should be your new favorite method.’

Trey Ideker, University of California, San Diego ‘Once again, Dan Gusfield has written an accessible book that shows that algorithmic rigor need not be sacrificed when solving real-world problems. He explains integer linear programming in the context of real-world biology. In doing so, the reader has an enriched understanding of both algorithmic details and the challenges in modern biology.’

Russ Altman, Stanford University, California 2019 253 x 177 mm 428pp 123 b/w illus.

978-1-108-42176-8 Hardback £49.99 / US$64.99 For all formats available, see

www.cambridge.org/9781108421768

Bioinformatics and Computational Biology in Drug Discovery and Development Edited by William T. Loging Mount Sinai School of Medicine, New York

Providing a comprehensive overview of the drug discovery and development pipeline, this book focuses on the integral role that computational biology methods play in this process. Covering technological advances and their relation to drug developmental processes, readers are exposed to new methods of discovery utilising the available technology.

‘We live in transformative times and perhaps big data and analytics represent a most interesting and essential concept of today. From the telescope to the microscope, our ability to peer into complexities of life has transformed humanity. Big data is the next major step in major transition. Bioinformatics and Computational Biology in Drug Discovery and Development is a road map to an inevitable future – a future where data define disease, diagnosis and drugs.

This book is an essential companion for anyone in drug development who has one foot in the present and one in the future.’

John Nosta, President, NOSTALAB 2018 244 x 170 mm 253pp 46 b/w illus. 9 colour illus. 3 tables 978-1-108-46115-3 Paperback £29.99 / US$39.99 For all formats available, see

www.cambridge.org/9781108461153

Computational Biology

7

Genome-Scale Algorithm Design Biological Sequence Analysis in the Era of High-Throughput Sequencing

Veli Mäkinen Djamal Belazzougui Fabio Cunial and Alexandru I. Tomescu University of Helsinki

Outlining the fundamental algorithms and data structures that power modern sequence analysis workflows, this book provides a powerful toolkit for students and researchers in bioinformatics and computer science. Its numerous examples and exercises are designed to help readers understand applications of the latest algorithm techniques, providing tools for further research.

Contents: Part I. Preliminaries; Part II. Fundamentals of Biological Sequence Analysis; Part III. Genome-Scale Index Structures; Part IV. Genome-Scale Algorithms; Part V. Applications.

‘Genome-Scale Algorithm Design is a well-thought-out … book that fills a gap in the recent literature … [on algorithms] for bioinformatics. It offers a sound, clear, and rich overview of computer science methods for the challenge of today’s biological sequence analysis. I [recommend] it to students as well as to researchers in the field.’

Nadia Pisanti, University of Pisa ‘This book will be a new reference text for string data structures and algorithms, as well as their applications in computational molecular biology and genome analysis. The technically precise style, illustrated with a great collection of welldesigned examples and many exercises, makes it an ideal resource for researchers, students, and teachers.’

Jens Stoye, Universität Bielefeld 2015 247 x 174 mm 413pp 90 b/w illus. 4 tables 269 exercises 978-1-107-07853-6 Hardback £44.99 / US$64.99 For all formats available, see

www.cambridge.org/9781107078536

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8

Computational Biology

Bayesian Evolutionary Analysis with BEAST Alexei J. Drummond University of Auckland

and Remco R. Bouckaert University of Auckland

A comprehensive overview of Bayesian approaches to phylogenetics using Markov chain Monte Carlo (MCMC) methods, offering theoretical insight, pragmatic advice and tools to develop further models. This title is a one-stop reference to applying the latest phylogenetic models in BEAST 2, interpreting the analyses and extending these models further.

Contents: Part I. Theory; Part II. Practice; Part III. Programming.

‘Want to construct a phylogeny, add in calibrated time points or work out the past history of an epidemic? The open source package BEAST has established itself as the industry standard for all this and more.

This definitive book, explaining what is under the hood, how the user can customize extensions and, most critically, a simple ‘how to’ users guide, is necessary reading for beginners and specialists alike.’

Laurence D. Hurst, University of Bath ‘In concert with the dramatic improvements to DNA sequencing technology, Bayesian inference has revolutionized population genetics, phylogenetics, and divergence time estimation. A similar impact on epidemiology appears imminent via a suite of new Bayesian methods that incorporate host and pathogen DNA sequence data into established mathematical frameworks. This book is an accessible and thorough introduction to these Bayesian procedures. However, the book does far more than explain the theory. It also includes clear guides on how to use the BEAST 2 software for performing Bayesian analyses, and how to visualize the results. Because the software is designed to be extensible, the book instructs users to write their own code to supplement the diverse methods that are already implemented in BEAST 2. This book is timely and is written by two of the leaders of the field. I highly recommend it.’

Jeff Thorne, North Carolina State University 2015 247 x 174 mm 260pp 21 b/w illus. 70 colour illus. 9 tables 978-1-107-01965-2 Hardback £42.99 / US$55.99 For all formats available, see

www.cambridge.org/9781107019652

Computational Neurobiology Data-Driven Computational Neuroscience Machine Learning and Statistical Models

Concha Bielza Universidad Politécnica de Madrid

and Pedro Larrañaga Universidad Politécnica de Madrid

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This modern treatment of real world cases offers neuroscience researchers and graduate students a comprehensive, in-depth guide to statistical and machine learning methods.

Contents: 2020 253 x 177 mm c.700pp 210 b/w illus. 40 colour illus.

978-1-108-49370-3 Hardback £69.99 / US$89.99 Publication August 2020 For all formats available, see

www.cambridge.org/9781108493703

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Brain Network Analysis Moo K. Chung University of Wisconsin, Madison

This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students.

‘This book is a must-read for students and researchers in brain network analysis. It is unique across many fronts. First, it weaves together the important background material in statistics, computational mathematics and algebraic topology. Second, it accomplishes the dual role of a research monograph and a textbook reference. The author, an expert in this field, conveys his enthusiasm for brain network analysis and lays down the most essential mathematical and statistical foundations for future advances.’

Hernando Ombao, King Abdullah University of Science and Technology, Saudi Arabia 2019 228 x 152 mm 338pp 41 colour illus.

978-1-107-18486-2 Hardback £59.99 / US$79.99 For all formats available, see

www.cambridge.org/9781107184862

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10

Computational Neurobiology

Neuronal Dynamics From Single Neurons to Networks and Models of Cognition

Wulfram Gerstner École Polytechnique Fédérale de Lausanne

Werner M. Kistler Richard Naud University of Ottawa

and Liam Paninski Columbia University, New York

Exploring neuron models, the neural code, decision making and learning, this textbook provides a thorough and up-to-date introduction to computational neuroscience for advanced undergraduate and beginning graduate students.

With step-by-step explanations, end-of-chapter summaries and classroomtested exercises, it is ideal for courses or for self-study.

Contents: Part I. Foundations of Neuronal Dynamics; Part II. Generalized Integrateand-Fire Neurons; Part III. Networks of Neurons and Population Activity; Part IV. Dynamics of Cognition.

2014 247 x 174 mm 578pp 280 b/w illus. 6 tables 80 exercises 978-1-107-63519-7 Paperback £37.99 / US$50.99 For all formats available, see

www.cambridge.org/9781107635197

Computational Neurobiology

11

Principles of Computational Modelling in Neuroscience David Sterratt University of Edinburgh

Bruce Graham University of Stirling

Andrew Gillies Psymetrix Limited, Edinburgh

and David Willshaw University of Edinburgh

This book is for neuroscientists at all levels and for people from the informational and physical sciences who want to develop computational models of the neuron and neural circuits. It presents the principles of computational neuroscience in a clear and coherent manner, and addresses practical issues that arise in modelling projects.

‘Here at last is a book that is aware of my problem, as an experimental neuroscientist, in understanding the maths … I expect it to be as mind expanding as my involvement with its authors was over the years. I only wish I had had the whole book sooner – then my students and post-docs would have been able to understand what I was trying to say and been able to derive the critical tests of the ideas that only the rigor of the mathematical formulation of them could have generated.’

Gordon W. Arbuthnott, Okinawa Institute of Science and Technology, Japan ‘This is a wonderful, clear and compelling text on mathematically-minded computational modelling in neuroscience. It is beautifully aimed at those engaged in capturing quantitatively, and thus simulating, complex neural phenomena at multiple spatial and temporal scales, from intracellular calcium dynamics and stochastic ion channels, through compartmental modelling, all the way to aspects of development. It takes particular care to define the processes, potential outputs and even some pitfalls of modelling, and can be recommended for containing the key lessons and pointers for people seeking to build their own computational models. By eschewing issues of coding and information processing, it largely hews to concrete biological data, and it nicely avoids sacrificing depth for breadth. It is very suitably pitched as a master’s level text, and its two appendices, on mathematical methods and software resources, will rapidly become dog-eared.’

Peter Dayan, University College London 2011 246 x 189 mm 404pp 178 b/w illus. 7 tables 978-0-521-87795-4 Hardback £49.99 / US$74.99 For all formats available, see

www.cambridge.org/9780521877954

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Genomics Topological Data Analysis for Genomics and Evolution Topology in Biology

Raul Rabadan Columbia University, New York

and Andrew J. Blumberg University of Texas, Austin

Algebraic topology is particularly suited for the analysis of high dimensional large data sets, including those in modern biology. The book introduces geometric and topological methods, including statistics, as well as applications to biology – including cancer genetics, single cell studies and reconstructing evolutionary relationships from genomic data.

Contents: Part I. Topological Data Analysis; Part II. Biological Applications.

‘The time is right to bring new approaches to the analysis of biological data.

Topological data analysis reveals the structure of data. This book shows how algebraic topology opens new doors, presenting ideas and directions that make testable predictions and explore life processes.’

Arnold J. Levine, Institute for Advanced Study, New Jersey ‘This fascinating book describes how advances in mathematics, especially in fields such as topology, are transforming our understanding of biology. Rabadan, one of the founders of the field, shows us how the evolution of cancer, and of viruses and bacteria, can be deeply understood through these novel mathematical techniques.

Rabadan’s capacity to create a synthesis of many threads, and lay out future challenges, makes this an intriguing and compelling read.’

Siddhartha Mukherjee, Columbia University Medical Center, New York and author of The Gene: An Intimate History and The Emperor of All Maladies: A Biography of Cancer 2019 247 x 174 mm 324pp 277 colour illus.

978-1-107-15954-9 Hardback £39.99 / US$49.99 For all formats available, see

www.cambridge.org/9781107159549

Genomics

13

Genome Editing and Engineering From TALENs, ZFNs and CRISPRs to Molecular Surgery

Edited by Krishnarao Appasani GeneExpression Systems, Inc.

Foreword by George M. Church

Endonuclease-based genomic engineering is a field with broad potential applications for the treatment of human disease. This complete reference covers the discovery, basic science and application, making it invaluable for researchers and graduate students across the biomedical sciences, and those in the biotechnology and pharmaceutical industries.

Contents: Part I. Biology of Endonucleases (Zinc-Finger Nuclease, TALENs and CRISPRs) and Regulatory Networks; Part II. Genome Editing in Model Organisms; Part III. Technology Development and Screening; Part IV. Genome Editing in Stem Cells and Regenerative Biology; Part V. Genome Editing in Disease Biology; Part VI. Legal (Intelluctual Property) and Bioethical Issues of Genome Editing.

‘This comprehensive book is welcome at this point of rapid growth in new technologies and discoveries such that keeping up with applications of genome engineering is challenging. Here we have both a general introduction to the field and to deep mechanisms and glimpses of future applications and ethical considerations – with gems for newcomers and experts alike.’

George M. Church, Harvard University, Massachusetts and Massachusetts Institute of Technology ‘Krishnarao Appasani has assembled a comprehensive series of up-to-date chapters on endonuclease-based genomic engineering by experts and practitioners. The book presents a wide range of topics from basic science, applications to genetic screens and diseases, and legal and ethical issues. The many potential applications across a wide range of organisms are well illustrated. The book will become a must have for any researchers in academia and industry trying to keep up with this fast-moving field.’

Norbert Perrimon, Harvard Medical School, Boston 2018 247 x 174 mm 498pp 122 b/w illus. 32 colour illus. 9 tables 978-1-107-17037-7 Hardback £130.00 / US$170.00 For all formats available, see

www.cambridge.org/9781107170377

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14

Genomics

Genome-Wide Association Studies From Polymorphism to Personalized Medicine

Edited by Krishnarao Appasani GeneExpression Systems, Inc., Massachusetts

Foreword by Stephen W. Scherer University of Toronto

and Peter M. Visscher University of Queensland

Genome-wide association studies (GWAS) will have increasing importance in the post-genomic era. This timely publication, written by leading experts from academia and industry, provides an essential overview for both established scientists and students, focusing on the use of GWAS in the context of disease biology and personalized medicine.

Contents: Part I. Genome-Wide Association Studies; Part II. Genome-Wide Studies in Disease Biology; Part III. Single Nucleotide Polymorphisms, Copy Number Variants, Haplotypes and eQTLs; Part IV. Next-Generation Sequencing Technology and Pharmacogenomics; Part V. Population Genetics and Personalized Medicine.

‘Genome-Wide Association Studies: From Polymorphism to Personalized Medicine, edited by Krishnarao Appasani, summarizes most elegantly the contributions of GWAS as a major discovery tool linking complex disease phenotypes to genetic variants and associated biological pathways and gene networks that were previously unknown.

GWAS has transformed the genetic landscape in complex disease and has informed us more about the genetic underpinnings of common diseases and pharmacogenomics traits than any other tool to date. The present book captures this development elegantly and is a pleasure to read.’

Hakon Hakonarson, University of Pennsylvania ‘From genotype to phenotype: this biological paradigm is now elucidated and extended to the vision of genomic medicine. This highly informative book combines the current knowledge of genome wide association studies with the pathophysiology, epidemiology of human disease, and health condition, especially, implicating in the development of personalized and precision medicine. The combination of technical, scientific, medical, and pharmaco-economic aspects supports the high value of this book for scientists and medical specialists working in the field.’

Christine Günther, Chief Executive Officer, apceth GmbH and Co. KG, Munich, Germany 2016 247 x 174 mm 432pp 67 b/w illus. 26 colour illus. 24 tables 978-1-107-04276-6 Hardback £127.00 / US$204.00 For all formats available, see

www.cambridge.org/9781107042766

Systems Biology NEW IN PAPERBACK

Systems Genetics Linking Genotypes and Phenotypes

Edited by Florian Markowetz Cancer Research UK Cambridge Institute

and Michael Boutros German Cancer Research Center, Heidelberg

Gathering contributions from leading scientists, both computational and experimental, this book shows how experimental perturbations can help us to understand the link between genotype and phenotype.

Researchers and graduate students in genetics, functional genomics, bioinformatics, computational biology, systems biology and biotechnology will find this a valuable and timely tool.

‘Since the completion of the Human Genome Project we hold the ‘book of life’ in our hands, but for the most part, we do not understand how to interpret it.

We lack an understanding of the grammar that it is written in. With this book the authors put together an impressive collection of chapters that provide insights into our current efforts to understand how genetic information is integrated, coordinated and ultimately assembled into biological systems. If you are interested in how to decipher the grammar of life this is a must read!’

Frank Buchholz, Technische Universität Dresden, Germany Cambridge Series in Systems Genetics

2020 244 x 170 mm c.270pp 101 b/w illus. 12 tables 978-1-108-79459-6 Paperback £29.99 / US$39.99 For all formats available, see

www.cambridge.org/9781108794596

15

The Inner Workings of Life Vignettes in Systems Biology

Eberhard O. Voit Georgia Institute of Technology

Comprised of short vignettes, this introductory text explains key concepts within a systems biology approach without resorting to mathematical equations or technical jargon. Suitable for students and researchers alike, this is the first book aimed at a more introductory level to systems biology.

‘Popular science books have enabled the public to gain an appreciation for advances in a variety of esoteric disciplines ranging from chaos theory to evolutionary biology. But we lack a ‘fun read’ for the emerging field of systems biology, which is bringing together computer scientists, physicists and biologists to figure out the complex inner workings of living cells. Eberhard O. Voit has filled that gap with his new book. Voit provides the reader with an insider’s tour of systems biology, providing us [with] a sense of how this exciting field will change our lives in the coming years. Impress and challenge your book club with this new offering.’

James J. Collins, Massachusetts Institute of Technology and Harvard University, Massachusetts ‘This delightful book provides a very readable overview of the emerging field of systems biology.

The author, an expert in the field, describes fundamental concepts and tools in systems biology in a conversational style that makes the material very accessible to non-experts and a joy to read. The combination of interesting conceptual information, humor, history, and anecdotes makes this book hard to put down. And no need to worry about the technical mathematics underlying much of systems biology; there is not a single equation in the book! So if you are interested in learning something about negative feedback loops, adaptation, small regulatory RNAs, -omics research, chaos, microarrays, data mining, genome-wide association studies, or a host of other concepts and tools without diving into the details, this is the book for you.’

Richard Bertram, Florida State University 2016 228 x 152 mm 218pp 978-1-316-60442-7 Paperback £19.99 / US$29.99 For all formats available, see

www.cambridge.org/9781316604427

16

Systems Biology

Dance to the Tune of Life Biological Relativity

Denis Noble University of Oxford

Challenging the common gene-centric approach to organisms, this book articulates a relativistic theory of biology. It is grounded in up-to-date biological research and rigorous application of mathematics to biology; however, it is presented in a nontechnical manner for the general reader, and requires no familiarity with complex biology, mathematics or philosophy.

‘Among its many merits, this remarkable book deserves to become a classic text in the philosophy of science. Almost alone among philosophers of science, Noble is a practising scientist; and unusually among practising scientists, he is an accomplished philosopher. His book brings out, with unparalleled clarity, how the scientific endeavour involves not only empirical inquiry but also conceptual structure. Noble shows how, on the negative side, popular presentations of sound biological results may be vitiated by bad metaphysics, and how, on the positive side, science and philosophy may extend the boundaries of knowledge by a unified epistemology. He ends, however, with a salutary warning that there may well be a limit to the human capacity to know the answers to ultimate questions.’

Sir Anthony Kenny, University of Oxford ‘I think this a marvellous book. Denis Noble emphasises that genes, organs and systems dance to the tune of the organism and its social and physical environment. He sets the relativity of biology in a remarkable scientific sweep, ranging from cosmology to human belief systems. He reminds me of another great biologist, C. H. Waddington, to whom Noble pays handsome tribute. Writing with clarity and charm, Noble attempts to break down silos of knowledge inhabited by scientists who fail to come out and engage with others. … Broadening minds in an era of intense specialisation is more important than ever. Noble deserves to be successful in his desire to do just that and I hope that he will be.’

Sir Patrick Bateson, University of Cambridge 2016 228 x 152 mm 302pp 21 b/w illus. 26 colour illus.

978-1-107-17624-9 Hardback £17.99 / US$24.95 For all formats available, see

www.cambridge.org/9781107176249

Systems Biology

17

Systems Biology Constraint-based Reconstruction and Analysis

Bernhard Ø. Palsson University of California, San Diego

Reflecting the latest developments, this textbook explains how quantitative and computable genotype-phenotype relationships can be built using a genomewide basis of information about the gene portfolio of an organism. It has been developed through extensive classroom use, providing a conceptual framework in addition to invaluable modelling tools and computational approaches.

Contents: Part I. Network Reconstruction; Part II. Mathematical Properties of Reconstructed Networks; Part III. Determining the Phenotypic Potential of Reconstructed Networks; Part IV. Basic and Applied Uses; Part V. Conceptual Foundations.

‘One of the defining challenges of systems biology is to determine the structures and mechanisms by which complex networks of genes, proteins and metabolites control cell processes and molecular dynamics. Bernhard Ø. Palsson is a leading pioneer in constructing and analyzing genome-scale models of such networks. Here Palsson offers students an insider’s guided tour of the concepts, principles and techniques underlying this emerging field. The book is brilliantly laid out and offers professors well-structured, much-needed material for a graduate-level course in systems biology and network science.’

James J. Collins, Massachusetts Institute of Technology ‘This is a real tour de force. With enormous clarity, Bernhard Ø. Palsson sets out the what, why and how of network and systems biology, and of the important role of genome-wide reconstructions – especially, to date, of metabolism – in realising it … this is a masterful survey of the field by one of its leading practitioners. The development is nicely logical … If you are interested in network biology at all, then this book is for you.’

Douglas Kell, University of Manchester 2015 247 x 174 mm 550pp 27 b/w illus. 244 colour illus. 45 tables 978-1-107-03885-1 Hardback £49.99 / US$79.99 For all formats available, see

www.cambridge.org/9781107038851

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18

Systems Biology

Models of Life Dynamics and Regulation in Biological Systems

Kim Sneppen Niels Bohr Institutet, Copenhagen

Focusing on simple models, this book describes methods for studying the quantitative aspects of life through physical modelling, using E. coli and phage lambda as key examples. It encompasses fields such as quantitative molecular biology, systems biology and biophysics, providing a tool for students from both biological and physical science backgrounds.

‘Models of Life is an insight of a physicist into biological regulatory mechanisms. It provides a quantitative basis of how many of the biological systems work. Using simple logic and mathematics, Kim Sneppen, a world renowned scientist and thinker, has created a must-read for investigators in quantitative biology. The book provides a clear explanation of triumphant experiments in a lucid way with crisp figures. The brilliance of the author’s analytical mind is on display when one sees how he explains some of the exciting paradigmatic regulatory systems, beginning with the basics of molecular biology. The book is also replete with intellectually challenging problem questions for readers, making the book an excellent text for students as well.’

Sankar Adhya, National Cancer Institute, Maryland ‘Kim Sneppen’s insightful book covers lots of ground in describing biological systems at different time and length scales and levels of resolution. Its different chapters unified by the author’s modeling philosophy are sure to be of interest to a very diverse group of readers … Readers interested in agent-based modeling will find it applies to systems as diverse as epigenetics, propagation of information and evolutionary patterns in fossil records. Dedicated chapters combine biophysics and systems biology of gene regulation and protein-protein interactions. The book provides especially deep coverage of biology of phages, bacteria and their interactions within ecosystems. It would make an excellent textbook for one or even several university courses on systems or evolutionary biology. In fact when teaching these courses I will use it heavily myself and recommend it to my students.’

Sergei Maslov, Brookhaven National Laboratory, New York 2015 247 x 174 mm 350pp 25 b/w illus. 193 colour illus. 5 tables 165 exercises 978-1-107-06190-3 Hardback £44.99 / US$72.99 For all formats available, see

www.cambridge.org/9781107061903

Phylogenetics Computational Phylogenetics An Introduction to Designing Methods for Phylogeny Estimation

Tandy Warnow

19

The Phylogenetic Handbook A Practical Approach to Phylogenetic Analysis and Hypothesis Testing

Second edition Edited by Philippe Lemey

University of Illinois, Urbana-Champaign

University of Oxford

A comprehensive account of basic and advanced material in phylogeny estimation, focusing on computational and statistical issues. No background in biology or computer science is assumed, and there is minimal use of mathematical formulas, making the book accessible to students from biology, computer science, statistics, and applied mathematics.

Marco Salemi

Contents: Part I. Basic Techniques; Part II. Molecular Phylogenetics.

2017 247 x 174 mm 394pp 58 b/w illus. 8 colour illus. 11 tables 250 exercises 978-1-107-18471-8 Hardback £46.99 / US$59.99 For all formats available, see

www.cambridge.org/9781107184718

University of California, Irvine

and Anne-Mieke Vandamme Katholieke Universiteit Leuven, Belgium

With a stronger focus on hypothesis testing, elaborate practical sections and recent versions of sequence analysis and software, this edition includes six new chapters. Topics on Bayesian inference, tree topology testing and the impact of recombination on phylogenies have been added as well as a detailed section on molecular adaptation.

Contents: Part I. Introduction; Part II. Data Preparation; Part III. Phylogenetic Inference; Part IV. Testing Models and Trees; Part V. Molecular Adaptation; Part VI. Recombination; Part VII. Population Genetics; Part VIII. Additional Topics.

2009 247 x 174 mm 750pp 57 b/w illus. 18 tables 978-0-521-73071-6 Paperback £47.99 / US$64.99 For all formats available, see

www.cambridge.org/9780521730716

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20

Biostatistics Biostatistics with R An Introductory Guide for Field Biologists

Jan Lepš University of South Bohemia, Czech Republic

and Petr Šmilauer University of South Bohemia, Czech Republic

A straightforward introduction on how to analyse data from the field of biological research and conservation. All chapters are supplemented by thoroughly explained R code demonstrating interpretation of the results. An ideal reference for students, researchers and professionals, as well as lecturers of undergraduate courses.

2020 247 x 174 mm c.384pp 978-1-108-48038-3 Hardback £69.99 / US$89.99 978-1-108-72734-1 Paperback £26.99 / US$34.99 Publication July 2020 For all formats available, see

www.cambridge.org/9781108480383

Applied Mixed Model Analysis A Practical Guide

Second edition Jos W. R. Twisk Universiteit van Amsterdam

This book explains all aspects of mixed model analysis without mathematical jargon, so that non-statisticians can understand the basic principles, analyze their own data, and interpret the results with confidence. Worked examples are analyzed with STATA, and all datasets are available for download, equipping readers to replicate the methods.

Practical Guides to Biostatistics and Epidemiology

2019 247 x 174 mm 246pp 978-1-108-48057-4 Hardback £99.99 / US$130.00 978-1-108-72776-1 Paperback £44.99 / US$59.99 For all formats available, see

www.cambridge.org/9781108480574

Biostatistics

21

A Course in Morphometrics for Biologists Geometry and Statistics for Studies of Organismal Form

Fred L. Bookstein University of Washington

This book teaches not only the ‘how’ for statistical analysis of organismal size and shape, but also the ‘when’ and the ‘why’. Aimed at graduate students and researchers, it covers the whole range of today’s best techniques while always emphasizing the ways that arithmetic leads to biological understanding.

‘This is a pioneering and outstanding book with its interdisciplinary style of presentation, which aids the reader’s understanding of morphometrics (shape analysis) and explains how to apply its tools. It does not hesitate to use a wide variety of subjects to achieve its objectives: statistics, algebra and arithmetic. To make it a hands-on text, it also provides S+ code of the tools described. The text is very user-friendly as it is written in an informal and accessible style. The book will be essential reading for researchers and students in the area; it demonstrates exquisite scholarship and I cannot recommend this text more highly.’

K. V. Mardia, University of Leeds ‘This is a unique book; one that not only provides the basic formulae and concepts for undertaking quantitative data analyses, but also explains and illustrates the origins of these concepts, the controversies they embody, their links to other branches of science, and the personalities behind their creation. It’s a marvellous tour de force and one I suspect few others could have written with such verve and authority. Required reading for anyone seeking to understand – and especially to teach – methods of linear data analysis generally and the analysis of morphological data in particular.’

Norman MacLeod, The Natural History Museum, London 2018 228 x 152 mm 544pp 978-1-107-19094-8 Hardback £64.99 / US$89.99 For all formats available, see

www.cambridge.org/9781107190948

eBooks available at www.cambridge.org/ebookstore

22

Biostatistics

Experimental Design for Laboratory Biologists Maximising Information and Improving Reproducibility

Stanley E. Lazic AstraZeneca

An ideal resource for anyone conducting lab-based biomedical research, this guide shows how to design reproducible experiments that have low bias, high precision and widely applicable results. It explores key ideas in experimental design, including reproducibility and replication, assesses common designs, and shows how to plan for success.

‘This is a wonderfully lucid introduction to experimental design, written by an author who is clearly aware of the pitfalls that exist for the unwary experimenter. The focus is on how to design experiments to ensure reproducible research, with many examples illustrating general principles that need to be understood to avoid error and bias. The coverage of statistical analysis follows on naturally from the design issues, and is amply illustrated with exercises in R. Highly recommended.’

Dorothy Bishop, University of Oxford ‘Worldwide there is a salient discussion about deficiencies in the validity and predictiveness of research in the life sciences. Indeed, a fullblown ‘reproducibility crisis’ has been proclaimed. Against this backdrop this important textbook is a timely and highly useful contribution in the pressing quest to improve the robustness, rigor, and reproducibility of current biological and preclinical research. Proper experimental design is the bedrock for obtaining reliable evidence. By providing the necessary conceptual know-how and practical knowledge, [this book] enables investigators in all stages of their careers to minimize bias and improve statistical power through proper design and analysis of their experiments. This volume is unique … [as] it is immensely readable and accessible even for those with little previous knowledge, in combining all relevant aspects in a practical, concise and comprehensive manner, and in its clear focus on factors that help to improve the quality of research.’

Ulrich Dirnagl, Charité University Hospital, Germany 2016 246 x 189 mm 422pp 124 b/w illus.

978-1-107-42488-3 Paperback £39.99 / US$51.99 For all formats available, see

www.cambridge.org/9781107424883

Cambridge Series in Statistical and Probabilistic Mathematics High-Dimensional Statistics

Predictive Statistics

A Non-Asymptotic Viewpoint

Analysis and Inference beyond Models

Martin J. Wainwright

Bertrand S. Clarke and Jennifer L. Clarke

University of California, Berkeley

Recent years have seen an explosion in the volume and variety of data collected in scientific disciplines from astronomy to genetics and industrial settings ranging from Amazon to Uber.

This graduate text equips readers in statistics, machine learning, and related fields to understand, apply, and adapt modern methods suited to large-scale data.

‘Non-asymptotic, high-dimensional theory is critical for modern statistics and machine learning. This book is unique in providing a crystal clear, complete and unified treatment of the area. With topics ranging from concentration of measure to graphical models, the author weaves together probability theory and its applications to statistics. Ideal for graduate students and researchers. This will surely be the standard reference on the topic for many years.’

Larry Wasserman, Carnegie Mellon University, Pennsylvania ‘Martin J. Wainwright brings his large box of analytical power tools to bear on the problems of the day – the analysis of models for wide data. A broad knowledge of this new area combines with his powerful analytical skills to deliver this impressive and intimidating work – bound to be an essential reference for all the brave souls that try their hand.’

Trevor Hastie, Stanford University, California Cambridge Series in Statistical and Probabilistic Mathematics, 48

2019 253 x 177 mm 568pp 49 b/w illus. 1 table 211 exercises 978-1-108-49802-9 Hardback £57.99 / US$79.99 For all formats available, see

www.cambridge.org/9781108498029

University of Nebraska, Lincoln

Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and ‘black box’ settings, with computed examples.

Contents: Part I. The Predictive View; Part II. Established Settings for Prediction; Part III. Contemporary Prediction.

‘Prediction, one of the most important practical applications of statistical analysis, has rarely been treated as anything more than an afterthought in most formal treatments of statistical inference. This important book aims to counter this neglect by a wholehearted emphasis on prediction as the primary purpose of the analysis. The authors cut a broad swathe through the statistical landscape, conducting thorough analyses of numerous traditional, recent, and novel techniques, to show how these are illuminated by taking the predictive perspective.’

Philip Dawid, University of Cambridge ‘The prime focus in statistics has always been on modeling rather than prediction; as a result, different prediction methods have arisen within different subfields of statistics, and a general, all-encompassing account has been lacking.

For the first time, this book provides such an account and, as such, it convincingly argues for the primacy of prediction. The authors consider a wide range of topics from a predictive point of view and I am impressed by both the breadth and depth of the topics addressed and by the unifying story the authors manage to tell.’

Peter Grünwald, Centrum Wiskunde & Informatica and Universiteit Leiden Cambridge Series in Statistical and Probabilistic Mathematics, 46

2018 253 x 177 mm 656pp 978-1-107-02828-9 Hardback £64.99 / US$84.99 For all formats available, see

www.cambridge.org/9781107028289

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24

Institute of Mathematical Statistics Textbooks Computational Bayesian Statistics

Statistical Modelling by Exponential Families

An Introduction

Rolf Sundberg

M. Antónia Amaral Turkman Carlos Daniel Paulino Universidade de Lisboa

and Peter Müller University of Texas, Austin

This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user’s guide for researchers and graduate students from beyond statistics.

‘An introduction to computational Bayesian statistics cooked to perfection, with the right mix of ingredients, from the spirited defense of the Bayesian approach, to the description of the tools of the Bayesian trade, to a definitely broad and very much up-to-date presentation of Monte Carlo and Laplace approximation methods, to a helpful description of the most common software. And spiced up with critical perspectives on some common practices and a healthy focus on model assessment and model selection. Highly recommended on the menu of Bayesian textbooks!’

Christian Robert, Université de Paris IX, Paris-Dauphine, and University of Warwick ‘This book aims to be a concise introduction to modern computational Bayesian statistics, and it certainly succeeds! The authors carefully introduce every main technique that is around and demonstrate its use with the appropriate software. Additionally, the book contains a readable introduction to Bayesian methods, and brings the reader up to speed within the field in no time!’

Håvard Rue, King Abdullah University of Science and Technology, Saudi Arabia Institute of Mathematical Statistics Textbooks, 11

2019 228 x 152 mm 254pp 12 b/w illus.

978-1-108-70374-1 Paperback £29.99 / US$39.99 For all formats available, see

www.cambridge.org/9781108703741

Stockholms Universitet

This readable, digestible introduction to exponential families of distributions covers the essential theory and demonstrates its use in applications. Containing a vast set of examples and numerous exercises, it is written for graduate students and researchers with a background in basic statistical inference.

‘Rolf Sundberg’s book gives attractive properties of the exponential family and illustrates them for a wide variety of applications. Definitions are concise and most propositions look directly appealing. The writing reflects the author’s experience in deriving results that are essential for good modelling and convincing inference. Thus, this book is indispensable for all data scientists, be they graduate students or experienced researchers.’

Nanny Wermuth, Chalmers tekniska högskola, Sweden Institute of Mathematical Statistics Textbooks, 12

2019 228 x 152 mm 296pp 22 b/w illus. 100 exercises 978-1-108-70111-2 Paperback £29.99 / US$39.99 For all formats available, see

www.cambridge.org/9781108701112

Epidemiology

25

Evidence-Based Diagnosis

Essential Epidemiology

An Introduction to Clinical Epidemiology

An Introduction for Students and Health Professionals

Second edition Thomas B. Newman University of California, San Francisco

Fourth edition Penelope Webb

and Michael A. Kohn

QIMR Berghofer Medical Research Institute

University of California, San Francisco

A rigorous yet engaging guide to understanding and choosing a range of diagnostic and prognostic tests. Topics explored include the diagnostic process, the reliability and accuracy of different tests and quantifying treatment benefits using randomized trails. Numerous worked examples and problems based on real situations support readers’ learning.

2020 234 x 156 mm c.405pp 978-1-108-43671-7 Paperback £37.99 / US$49.99 For all formats available, see

www.cambridge.org/9781108436717

Chris Bain and Andrew Page Western Sydney University

Now in its fourth edition, Essential Epidemiology is an engaging and accessible introduction to the foundations of epidemiology. It addresses the study of infectious and chronic diseases, public health and clinical epidemiology, and the role of epidemiology in a range of health monitoring and research activities.

• Contains over ninety questions and answers to work through in the print book, and hundreds more in the interactive eBook 2020 255 x 190 mm c.504pp 171 colour illus. 61 tables 978-1-108-76680-7 Print/online bundle £57.00 / US$74.99 For all formats available, see

www.cambridge.org/9781108766807

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26

Data Science & Machine Learning Mathematics for Machine Learning Marc Peter Deisenroth University College London

A. Aldo Faisal Imperial College London

and Cheng Soon Ong Data61, CSIRO

This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

‘This book provides great coverage of all the basic mathematical concepts for machine learning. I’m looking forward to sharing it with students, colleagues, and anyone interested in building a solid understanding of the fundamentals.’

Joelle Pineau, McGill University, Montreal ‘The field of machine learning has grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This comprehensive text covers the key mathematical concepts that underpin modern machine learning, with a focus on linear algebra, calculus, and probability theory. It will prove valuable both as a tutorial for newcomers to the field, and as a reference text for machine learning researchers and engineers.’

Christopher Bishop, Microsoft Research Cambridge 2020 253 x 177 mm c.398pp 3 b/w illus. 106 colour illus.

978-1-108-45514-5 Paperback £35.99 / US$46.99 For all formats available, see

www.cambridge.org/9781108455145

Data Science & Machine Learning

27

A Hands-On Introduction to Data Science Chirag Shah University of Washington

A practical introduction to data science with a low barrier entry, this textbook is well-suited to students from a range of disciplines. Assuming no prior knowledge of the subject, the hands-on exercises and real-life application of popular data science tools are accessible even to students without a strong technical background.

Contents: Part I. Introduction; Part II. Tools; Part III. Machine Learning; Part IV. Applications and Evaluations.

‘Chirag’s extensive experience as a teacher shines through in this textbook, which lives up to its promise to be a ‘hands on’ introduction to data science.

Students have a chance to apply their learning to real-life examples from diverse fields, with hands-on examples that build on basic techniques and utilize tools of data science practice throughout the book. I am particularly pleased to see him weave human issues into his approach, putting principles ahead of particular tools and pointing to ethical challenges at various stages of working with data to help his audience develop an appreciation of ways context and interpretation shape data practices. He exposes students to a more nuanced perspective in which human as well as machine input shapes data science outcomes. It is an awareness that we all will need if we are to use data appropriately to tackle the complex challenges we face today.’

Theresa Dirndorfer Anderson ‘Dr. Shah has written a fabulous introduction to data science for a broad audience. His book offers many learning opportunities, including explanations of core principles, thought-provoking conceptual questions, and hands-on examples and exercises. It will help readers gain proficiency in this important area and quickly start deriving insights from data.’

Ryen W. White, Microsoft Research AI 2020 246 x 189 mm c.424pp 5 b/w illus. 135 colour illus. 36 tables 154 exercises 978-1-108-47244-9 Hardback £39.99 / US$49.99 For all formats available, see

www.cambridge.org/9781108472449

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28

Data Science & Machine Learning

A First Course in Network Science Filippo Menczer Santo Fortunato and Clayton A. Davis Indiana University, Bloomington

A practical introduction to network science suitable for students studying diverse programs such as business, cognitive science, neuroscience, sociology, biology, and engineering. A wide range of examples and exercises develop readers’ understanding, and Python programming tutorials provided online reinforce coding skills.

‘A First Course in Network Science by Menczer, Fortunato, and Davis is an easy-to-follow introduction into network science. An accessible text by some of the best-known practitioners of the field, offering a wonderful place to start one’s journey into this fascinating field, and its potential applications.’

Albert-László Barabási, Dodge Distinguished Professor of Network Science, Northeastern University ‘Should be titled the ‘Joy of Networks’, clearly conveys the fun and power of the science of networks, while providing extensive hands-on exercises with network data.’

David Lazer, University Distinguished Professor of Political Science and Computer and Information Science, Northeastern University 2020 246 x 189 mm c.300pp 131 b/w illus. 131 colour illus.

978-1-108-47113-8 Hardback £34.99 / US$44.99 For all formats available, see

www.cambridge.org/9781108471138

Data Science & Machine Learning

Foundations of Data Science Avrim Blum Toyota Technical Institute at Chicago

John Hopcroft Cornell University, New York

and Ravindran Kannan Microsoft Research, India

This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data.

The material in this book will provide students with the mathematical background they need for further study and research in machine learning, data mining, and data science more generally.

‘This beautifully written text is a scholarly journey through the mathematical and algorithmic foundations of data science. Rigorous but accessible, and with many exercises, it will be a valuable resource for advanced undergraduate and graduate classes.’

Peter Bartlett, University of California, Berkeley ‘The rise of the Internet, digital media, and social networks has brought us to the world of data, with vast sources from every corner of society. Data Science – aiming to understand and discover the essences that underlie the complex, multifaceted, and high-dimensional data – has truly become a ‘universal discipline’, with its multidisciplinary roots, interdisciplinary presence, and societal relevance. This timely and comprehensive book presents – by bringing together from diverse fields of computing – a full spectrum of mathematical, statistical, and algorithmic materials fundamental to data analysis, machine learning, and network modeling.

29

Foundations of Data Science offers an effective roadmap to approach this fascinating discipline and engages more advanced readers with rigorous mathematical/algorithmic theory.’

Shang-Hua Teng, University of Southern California 2020 253 x 177 mm 432pp 978-1-108-48506-7 Hardback £38.99 / US$49.99 For all formats available, see

www.cambridge.org/9781108485067

Mining of Massive Datasets Third edition Jure Leskovec Stanford University, California

Anand Rajaraman Rocketship VC

and Jeffrey David Ullman Stanford University, California

Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

2019 244 x 170 mm c.565pp 76 b/w illus. 250 exercises 978-1-108-47634-8 Hardback £59.99 / US$74.99 For all formats available, see

www.cambridge.org/9781108476348

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30

Data Science & Machine Learning

Machine Learning Refined Foundations, Algorithms, and Applications

Second edition Jeremy Watt Reza Borhani and Aggelos K. Katsaggelos Northwestern University, Illinois

An intuitive approach to machine learning detailing the key concepts needed to build products and conduct research. Featuring color illustrations, real-world examples, practical coding exercises, and an online package including sample code, data sets, lecture slides, and solutions. It is ideal for graduate courses, reference, and self-study.

Contents: Part I. Mathematical Optimization; Part II. Linear Learning; Part III. Nonlinear Learning; Part IV. Appendices.

‘An excellent book that treats the fundamentals of machine learning from basic principles to practical implementation. The book is suitable as a text for senior-level and first-year graduate courses in engineering and computer science. It is well organized and covers basic concepts and algorithms in mathematical optimization methods, linear learning, and nonlinear learning techniques. The book is nicely illustrated in multiple colors and contains numerous examples and coding exercises using Python.’

John G. Proakis, University of California, San Diego ‘Some machine learning books cover only programming aspects, often relying on outdated software tools; some focus exclusively on neural networks; others, solely on theoretical foundations; and yet more books detail advanced topics for the specialist.

This fully revised and expanded text provides a broad and accessible introduction to machine learning for engineering and computer science students. The presentation builds on first principles and geometric intuition, while offering real-world examples, commented implementations in Python, and computational exercises. I expect this book to become a key resource for students and researchers.’

Osvaldo Simeone, Kings College London 2020 247 x 174 mm 594pp 316 colour illus. 127 exercises 978-1-108-48072-7 Hardback £52.99 / US$69.99 For all formats available, see

www.cambridge.org/9781108480727

Data Science & Machine Learning

31

Computer Age Statistical Inference Algorithms, Evidence, and Data Science

Bradley Efron and Trevor Hastie Stanford University, California

Computing power has revolutionized the theory and practice of statistical inference. This book delivers a concentrated course in modern statistical thinking by tracking the revolution from classical theories to the large-scale prediction algorithms of today. Anyone who applies statistical methods to data will benefit from this landmark text.

Contents: Part I. Classic Statistical Inference; Part II. Early Computer-Age Methods; Part III. Twenty-First Century Topics.

‘How and why is computational statistics taking over the world? In this serious work of synthesis that is also fun to read, Efron and Hastie, two pioneers in the integration of parametric and nonparametric statistical ideas, give their take on the unreasonable effectiveness of statistics and machine learning in the context of a series of clear, historically informed examples.’

Andrew Gelman, Columbia University, New York ‘This unusual book describes the nature of statistics by displaying multiple examples of the way the field has evolved over the past sixty years, as it has adapted to the rapid increase in available computing power. The authors’ perspective is summarized nicely when they say, ‘very roughly speaking, algorithms are what statisticians do, while inference says why they do them’. The book explains this ‘why’; that is, it explains the purpose and progress of statistical research through a close look at many major methods, methods the authors themselves have advanced and studied at great length. Both enjoyable and enlightening, Computer Age Statistical Inference is written especially for those who want to hear the big ideas, and see them instantiated through the essential mathematics that defines statistical analysis. It makes a great supplement to the traditional curricula for beginning graduate students.’

Rob Kass, Carnegie Mellon University, Pennsylvania Institute of Mathematical Statistics Monographs, 5

2016 228 x 152 mm 495pp 5 b/w illus. 40 colour illus. 50 tables 978-1-107-14989-2 Hardback £45.99 / US$74.99 For all formats available, see

www.cambridge.org/9781107149892

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32

Programming Python by Example Learning to Program in 150 Challenges

Nichola Lacey Nichola Wilkin Ltd, Cambridge

A refreshingly different and engaging way of learning how to program using Python. This book includes example code and brief user-friendly explanations, along with 150 progressively trickier challenges.

As readers are actively involved in their learning, they quickly master the new skills and gain confidence in creating their own programs.

Contents: Part I. Learning Python; Part II. Chunky Challenges.

2019 276 x 219 mm c.191pp 140 b/w illus. 10 tables 978-1-108-71683-3 Paperback £16.99 / US$22.95 For all formats available, see

www.cambridge.org/9781108716833

A First Course in Statistical Programming with R Second edition W. John Braun University of British Columbia, Okanagan

and Duncan J. Murdoch University of Western Ontario

A new edition of a bestselling text, this book provides a first course in programming for a broad range of students who need to work with data.

Based on the open-source R statistical package, it introduces statistical graphics and numerical computing ideas such as simulation, optimization, and computational linear algebra.

‘For what has come to be called data analytics, R is a remarkable tour de force.

Strong skills with R programming are needed to allow really effective use.

Mastering the content of this carefully staged text is an excellent starting point for gaining those skills.’

John Maindonald, Australian National University, Canberra ‘This book should be especially useful for those without any prior programming background. The core programming material, such as loops and functions, is postponed to Chapter 4, allowing the student to first become comfortable with R in a broader manner. The placement of Chapter 3, on graphical methods, is particularly helpful in this regard, and is very motivating. The book is written by two recognized experts in the R language, so the reader attains the benefit of being taught by the ‘insiders’.’

Norm Matloff, University of California, Davis 2016 246 x 189 mm 230pp 40 b/w illus. 5 colour illus. 200 exercises 978-1-107-57646-9 Paperback £34.99 / US$44.99 For all formats available, see

www.cambridge.org/9781107576469

Programming

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Python Programming for Biology Bioinformatics and Beyond

Tim J. Stevens MRC Laboratory of Molecular Biology, Cambridge

and Wayne Boucher University of Cambridge

This book presents core concepts in computational biology in an accessible, jargon-free manner and offers a complete foundation course in the Python language, with entry points for novices and experienced programmers alike.

Material covers traditional bioinformatics and many topics beyond, with practical examples for Python versions 2 and 3.

‘As a long-time advocate of Python as the language of choice for both the bulk of biological data analysis and for teaching computer programming to molecular life scientists, I am delighted to see this book. [It] provides a well-focused introduction to Python programming but then goes on to use the clarity of the Python language to demystify a wide range of commonly applied data processing and analysis techniques that arise in modern cell and molecular biology. The integration of straightforward introductions to sequence analysis, image processing and statistical analysis (amongst others) into a book on Python is inspired. The clarity of the Python language helps to show that often ‘yes it really is that simple’, in a way that staring at a mathematical expression often fails to, and the programming element allows the reader to become actively involved.’

Jeremy Craven, University of Sheffield ‘Python Programming for Biology is an excellent introduction to the challenges that biologists and biophysicists face. The choice of Python is appropriate; we use it in most research in our laboratories at the interface between biology, biochemistry and bioinformatics. The book takes us through programming principles for a beginner with a biological background, introducing the basics. It has useful tips for improving code and some specific examples, for example in sequence analysis, macromolecular structures, image processing and databases. I was pleased to see that there is a substantive section on machine learning which in the era of ‘big data’ is becoming central to much of the software developed for biomedical and agri-biotech research.’

Tom Blundell, University of Cambridge 2015 247 x 174 mm 711pp 91 b/w illus. 11 colour illus. 3 tables 978-0-521-72009-0 Paperback £45.99 / US$64.99 For all formats available, see

www.cambridge.org/9780521720090

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34

Programming

Computing for Biologists Python Programming and Principles

Ran Libeskind-Hadas Harvey Mudd College, California

and Eliot Bush Harvey Mudd College, California

Specifically designed for life science students with no prior computing experience, this textbook teaches computational problem-solving along with Python programming skills. The chapters cover three key tools – gene finding, sequence alignment and phylogenetic methods. An accompanying website features numerous integrated exercises, equipping students with the skills to write programs independently.

Contents: Part I. Python versus Pathogens; Part II. Sequence Alignment and Sex Determination; Part III. Phylogenetic Reconstruction and the Origin of Modern Humans; Part IV. Additional Topics.

‘In my twenty years as a professor, I have never run across a textbook on bioinformatics algorithms that a biologist can read from cover to cover and understand. This is the one.’

Pavel Pevzner, Ronald R. Taylor Distinguished Professor of Computer Science, University of California, San Diego ‘This is an awesome book for anyone to get into computing. It is easy to follow and clearly structured so the reader understands what they are learning and why.

The book provides the fundamentals concepts of computational biology and bioinformatics in parallel to gaining actual skills in computing and the ability to write your own Python programs! What I love about the book is how the authors ensure the concepts and skills are applicable to a clear and defined biological problem. The authors help demystify the various topics and bring the reader to understand the algorithms behind the programming tools by applying these to resolve an actual biological problem. This book is also an excellent resource for those involved in training and education, and it provides plenty of exercise to use in the actual classroom.’

Maria Victoria Schneider, The Genome Analysis Centre (TGAC), UK 2014 246 x 189 mm 218pp 8 b/w illus. 33 colour illus. 1 table 978-1-107-64218-8 Paperback £37.99 / US$49.99 For all formats available, see

www.cambridge.org/9781107642188

Of related interest Single-Molecule Science From Super-Resolution Microscopy to DNA Mapping and Diagnostics

Edited by Krishnarao Appasani GeneExpression Systems, Inc.

and Raghu Kiran Appasani University of Southern California Keck School of Medicine

Bridging biophysics and molecular imaging, this authoritative text guides readers through the use of single molecule approaches in the study of molecular nanomachines, protein folding, biological assemblies, gene expression, and DNA mapping for diagnostic purposes. A must-have for researchers, graduate students, and those working in the industry.

2020 247 x 174 mm c.550pp 34 b/w illus. 1 table 978-1-108-42336-6 Hardback c. £125.00 / c. US$159.99 Publication August 2020 For all formats available, see

www.cambridge.org/9781108423366

Optogenetics From Neuronal Function to Mapping and Disease Biology

Edited by Krishnarao Appasani GeneExpression Systems, Inc., Massachusetts

Optogenetics – a revolutionary technique combining genetic and optical methods to observe and control the function of neurons – has huge potential, with applications from brain circuits and sleep to neurodegenerative and neuropsychiatric diseases. This book is a reference for researchers and graduate students, as well as for those working in the biotechnology and pharmaceutical industries.

Contents: Part I. Optogenetics in Model Organisms; Part II. Opsin Biology, Tools and Technology Platform; Part III. Optogenetics in Neurobiology, Brain Circuits and Plasticity; Part IV. Optogenetics in Learning, Neuro-psychiatric Diseases and Behavior; Part V. Optogenetics in Vision Restoration and Memory; Part VI. Optogenetics in Sleep, Prosthetics and Epigenetics of Neurodegenerative Diseases.

‘Optogenetics has transformed neuroscience and has become a key element of the toolkit used by thousands of labs worldwide. If anyone needs convincing that the field of optogenetics has come of age, this book provides compelling evidence. Written by leading experts in the field and covering the gamut of optogenetics research from tool development and use in basic research through to translational applications, Optogenetics exemplifies how this technique now illuminates all areas of neuroscience research.’

Michael Hausser, University College London, ‘’Let there be light’. Or more precisely, deliver the needed wavelength at appropriate power, with high temporal and spatial resolution if you want to figure out how brain circuits work. This volume has many excellent chapters and the right toolbox for the job.’

György Buzsáki, Neuroscience Institute and Langone Medical Center, New York University 2017 247 x 174 mm 502pp 65 b/w illus. 37 colour illus. 6 tables 978-1-107-05301-4 Hardback £131.00 / US$184.00 For all formats available, see

www.cambridge.org/9781107053014

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36

Of related interest

HIGHLIGHT

Understanding Coronavirus Raul Rabadan Columbia University, New York

Why is the information available about the coronavirus/COVID-19 so confusing? Written by a leading researcher, Understanding Coronavirus is a concise and accessible introduction to all the science and facts you need to understand how the virus works, how it spreads and how it compares to other respiratory viruses.

‘With all the technology and medical knowledge of the 21st century a pandemic virus has defeated us. This book tells us why and how that could happen and what we can do about it. And as a bonus we get a comparison with the 1918 pandemic Flu. All this wrapped up in a clear, understandable and interesting way. We learn what is happening to us now and how to better prepare for the future.’

Arnold J. Levine, Institute for Advanced Study, Princeton, New Jersey ‘An extremely concise and important book that everyone should read to understand the dynamics of the COVID-19 pandemic.’

Siddhartha Mukherjee, Columbia University, New York, and author of The Gene and The Emperor of All Maladies ‘Raul Rabadan has written an essential book for the first pandemic of the 21st century, COVID19 caused by SARS-CoV-2. It’s a wonderfully concise and accessible explanation of everything you want to know about the virus, the disease, and the outbreak. If you want to learn what is a coronavirus, how the outbreak started, what are the therapeutic options, and much more, I highly recommend this book. Professor Rabadan explains viruses in a way that is accessible to all.’

Vincent Racaniello, Columbia University, New York Understanding Life

2020 178 x 127 mm c.120pp 978-1-108-82671-6 Paperback £9.99 / US$11.99 For all formats available, see

www.cambridge.org/9781108826716

Of related interest

Understanding Evolution Second edition Kostas Kampourakis University of Geneva

Philosophy of Science for Biologists Edited by Kostas Kampourakis Université de Genève

What is evolution and why do so many people find it difficult to understand? Understanding Evolution is a concise and accessible introduction to the core concepts of evolutionary theory, presented in the light of common conceptual obstacles. It shows that there is more than religious resistance to accepting evolution.

and Tobias Uller

‘While other books explain what is wrong with the popular attacks on evolution – e.g. creationism, or Intelligent Design – this concise book addresses the fundamental question: why do people fail to accept evolution? This is like going deep to the causes of the illness, while others just try to lower the fever.’

Alessandro Minelli, University of Padova, Italy, and author of Plant Evolutionary Developmental Biology

‘As a philosopher and a biologist I have been waiting for a long time for a book like this to come out. My students will learn a lot from it.’

Massimo Pigliucci, K.D. Irani Professor of Philosophy, City College of New York

‘A well-known philosopher of biology once wrote that evolutionary theory seems so simple that almost anyone can misunderstand it. In this heartfelt yet thoughtful book, Kostas Kampourakis essentially turns that sentiment on its head.’

John C. Avise, Distinguished Professor of Ecology and Evolution, University of California–Irvine, and author of Evolutionary Pathways in Nature: A Phylogenetic Approach.

Understanding Life

2020 178 x 127 mm c.300pp 7 tables 978-1-108-74608-3 Paperback £12.00 / US$14.95 Publication August 2020

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Lunds Universitet, Sweden

Written for students and researchers in the life sciences, this is the first book to provide an accessible introduction to philosophy of science with a focus on biology. It draws on contemporary examples to enable biologists to become more philosophically minded and informed, facilitating all aspects of research and communication.

‘Philosophy of Science for Biologists is a muchawaited book written for biologists, mainly for curious and open-minded biology students.

Presenting a broad spectrum of perspectives and many fascinating examples from all areas of biology, the fifteen essays in this book offer a broad and exciting vista of biological ideas, their scope, their ambitions and their potential prejudices. The essays illustrate how a multiplicity of perspectives and methodologies can be combined to answer difficult questions, encouraging cooperation, healthy skepticism and necessary optimism. It should be the basis of an obligatory course for all biology students.’

Eva Jablonka, Cohn Institute for the History and Philosophy of Science and Ideas, Tel Aviv University 2020 244 x 170 mm c.275pp 1 b/w illus. 2 tables 978-1-108-74070-8 Paperback £26.99 / US$34.99 Publication July 2020 For all formats available, see

www.cambridge.org/9781108740708

For all formats available, see

www.cambridge.org/9781108746083

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Of related interest

Prokaryotic Metabolism and Physiology

NEW IN PAPERBACK

Fred Sanger – Double Nobel Laureate

Second edition Byung Hong Kim

A Biography

Korea Institute of Science and Technology, Seoul

University of Oxford

and Geoffrey Michael Gadd

University of Oxford

University of Dundee

Our biosphere is shaped by vast numbers of different prokaryotic microorganisms which show extremely diverse metabolic capabilities. This book provides an up-to-date overview of the metabolic processes that occur in bacteria and archaea, and the key processes that determine their roles in the environment, biotechnology and human health.

‘Overall this is an excellent text for researchers to refer to and for more advanced students to understand the complexities that are presented by prokaryotic organisms.’

Ellis O’Neill, The Biologist 2019 246 x 189 mm 504pp 373 b/w illus. 60 tables 978-1-107-17173-2 Hardback £130.00 / US$175.00 978-1-316-62291-9 Paperback £49.99 / US$69.99 For all formats available, see

www.cambridge.org/9781107171732

George G. Brownlee Foreword by Edwin Southern

Drawing, in part, on a rare interview by the author, this is the first full biography of Fred Sanger to be published. Brownlee highlights the remarkable extent of Sanger’s scientific achievements, providing a real portrait of the man behind them and considering his continuing legacy as ‘the father of genomics’.

‘Fred Sanger’s innovation and achievements enabled us to read the code of life. His breakthroughs transformed science, medicine, industry and society, and continue to open our eyes to a new knowledge and understanding of how life works … This book provides a rare opportunity to see a glimpse of a remarkable man who changed the world.’

David Bentley, Vice-President and chief scientist, Illumina Inc., Cambridge ‘Every student of molecular biology would profit greatly by lingering over Sanger’s own descriptions of the several strategies he attempted and the tools he had to invent to arrive at what is referred to today as Sanger DNA Sequencing …

Sanger’s success transformed molecular biology in inestimable ways and his methodology is equally foundational in such varied fields as evolutionary biology, plant breeding, paleontology, anthropology, linguistics, forensics and computer science … Fred Sanger was motivated by the challenge of discovery and believed fervently that through art and science, in their broadest senses, it is possible to make a lasting contribution towards the improvement and enrichment of human life.’

Paul Berg, Stanford University, California 2020 229 x 152 mm c.224pp 94 b/w illus. 8 colour illus.

978-1-108-79453-4 Paperback £18.99 / US$24.99 For all formats available, see

www.cambridge.org/9781108794534

Of related interest

Wilson and Walker’s Principles and Techniques of Biochemistry and Molecular Biology Eighth edition Edited by Andreas Hofmann Griffith University, Queensland

and Samuel Clokie Birmingham Women’s and Children’s Hospital

This best-selling undergraduate textbook introduces the key experimental techniques from across the biosciences. It uniquely integrates the theories and methods driving the fields of biology and medicine, comprehensively covering both the techniques that students will encounter in lab classes and those that underpin recent advances and discoveries.

‘After seven editions between 1975 and 2010 this essential textbook has undergone a major update.

The new editors, Drs Hofmann and Clokie, recruited many experts to revise individual chapters and added a significant amount of new material, thus making the book even more valuable. This eighth edition is basically a new book that covers the techniques of biochemistry and molecular biology in a very comprehensive manner – it does not go into great detail, but gives the reader a good introduction to all of them. Each chapter contains suggestions for further reading for those in need of a follow-up. Excellent diagrams and illustrations provide help in comprehension of the presented material. Since this text is largely aimed at undergraduate students, it fulfils its role extremely well.’

Alexander Wlodawer, National Cancer Institute at Frederick Review from previous edition: ‘This book deserves a place in any modern pathology department and brings together a body of information which is traditionally scattered across several texts … it also represents excellent value for money.’

Annals of Clinical Biochemistry 2018 247 x 174 mm 956pp 374 colour illus.

978-1-107-16227-3 Hardback £117.00 / US$152.99 978-1-316-61476-1 Paperback £39.99 / US$51.99 For all formats available, see

www.cambridge.org/9781107162273

Leading your Research Team in Science Ritsert C. Jansen Rijksuniversiteit Groningen, The Netherlands

This short and practical guide offers valuable recommendations, stories and exercises, to guide readers towards a really successful career as an independent investigator in science. A must-read for earlycareer researchers, as well as those advising them and anyone else serious about science. This title is available as Open Access via Cambridge Core.

Contents: Part I. Team; Part II. Organization; Part III. Society.

2018 228 x 152 mm 230pp 21 b/w illus.

978-1-108-70186-0 Paperback £18.99 / US$24.99 For all formats available, see

www.cambridge.org/9781108701860

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40

Of related interest

Funding your Career in Science

Developing a Talent for Science

From Research Idea to Personal Grant

Ritsert C. Jansen

Ritsert C. Jansen

Rijksuniversiteit Groningen, The Netherlands

Rijksuniversiteit Groningen, The Netherlands

How can you make the most of your talent for science? This practical guide offers valuable recommendations, real-life stories and practical exercises to enable students, postdoctorates and professors to develop their skills and succeed in academia, industry or elsewhere.

How can you get the funding to establish or consolidate a career in science? This concise guide offers step-by-step advice, real-life stories and practical exercises to help you prepare effective career grant applications and optimise your funding opportunities.

A must-read for students, postdocs, professors, and anyone else serious about science.

‘This is a well-written text for the purposes of enlightening the readership on proposal writing. I highly recommend it for use by those in the early stages of seeking funding for their careers in science and engineering.’

IEEE Pulse ‘… a practical guide aimed primarily at early career academics considering the major challenge of writing applications for project grant and fellowship funding.

With success rates for proposals reduced to an all-time low, help on how to be competitive is precious … strongly recommended if you are a postgraduate biology student, postdoc or young group leader.’

Andrew Taylor-Robinson, The Biologist 2013 228 x 152 mm 215pp 15 b/w illus.

978-1-107-62417-7 Paperback £18.99 / US$28.99 For all formats available, see

www.cambridge.org/9781107624177

‘This insightful book offers guidance toward an enhanced productive academic or professional scientific career … a must-read for any professional in the geophysical community and for those pursuing studies in this field.’

The Leading Edge ‘… if you had only one book to recommend to a student I would suggest this one. It is all there: the tips that, if applied, will make you a good presenter, an inspiring communicator, a soughtafter collaborator, and more.’

Elements 2011 228 x 152 mm 180pp 20 b/w illus.

978-0-521-14961-7 Paperback £18.99 / US$28.99 For all formats available, see

www.cambridge.org/9780521149617

Of related interest

Modern Prometheus Editing the Human Genome with Crispr-Cas9

Jim Kozubek Massachusetts Institute of Technology

Would you change your genes if you could? Crispr-Cas9 technologies are now offering cheap and effective methods for editing the human genome. Telling the interwoven stories of the scientists involved, Kozubek traces events across a fifty-year period, demystifying how Crispr works and reflecting on the continuing ethical dilemmas it brings, detailing all the very latest in this updated paperback edition.

2018 228 x 152 mm 474pp 978-1-108-45462-9 Paperback £14.99 / US$19.95 For all formats available, see

www.cambridge.org/9781108454629

The Cell as a Machine Michael Sheetz Columbia University, New York

and Hanry Yu National University of Singapore

Connecting underlying theory with real-world applications, this systematic and mathematically accessible textbook explains cell functions using the engineering principles of robust devices. It is ideal for undergraduate and graduate students taking single-

41

semester courses in cell mechanics, biophysics and cell biology.

Contents: Part I. Principle of Complex Function in Robust Machines; Part II. Design and Operation of Complex Functions; Part III. Coordination of Complex Functions.

Cambridge Texts in Biomedical Engineering

2018 246 x 189 mm 434pp 2 b/w illus. 136 colour illus.

978-1-107-05273-4 Hardback £69.99 / US$91.99 For all formats available, see

www.cambridge.org/9781107052734

Biophysics of DNA Alexander Vologodskii New York University

Designed to enable students and researchers of molecular biology, biochemistry and physics to better understand the biophysics of DNA, this text surveys the very latest research.

The author integrates theoretical and experimental approaches, emphasizing the importance of quantitative knowledge of physical properties in building and analyzing models of DNA functioning.

2015 247 x 174 mm 272pp 155 b/w illus. 16 colour illus. 9 tables 978-1-107-03493-8 Hardback £75.00 / US$99.99 For all formats available, see

www.cambridge.org/9781107034938

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42

Of related interest

Aaron Klug – A Long Way from Durban A Biography

Kenneth C. Holmes Max-Planck-Institut für Medizinische Forschung, Heidelberg

A Nobel prize winner and pioneer of structural molecular biology, Aaron Klug served as Director of the Laboratory of Molecular Biology and President of the Royal Society. Holmes draws on their long-term collaboration, interviews and unique access to Klug’s archives to illuminate both his personal life and significant scientific achievements.

Contents: Part I. From Durban to Birkbeck College; Part II. Science at the Laboratory of Molecular Biology; Part III. Duties and Rewards.

‘This biography highlights both the sense in which Klug was self-made and driven, and the importance of his collaborations, mentors, peers and his own students in shaping the man he became and his intellectual achievements.

The biography also offers a fascinating insight into macromolecular scientific discovery while keeping a very human touch throughout. A fitting tribute to a great scientist and role model.’

Max Price, University of Cape Town ‘Kenneth C. Holmes’ lively biography of Aaron Klug narrates the fascinating story of a man who had a central role in the transformation of modern biology into a molecular science. Holmes embeds Klug’s scientific innovations in the wider context of mid-to-late twentieth-century intellectual and social history; his descriptions of the left-wing Zionism of Klug’s youth in South Africa and of the machinations of reactionary dons in Peterhouse, Cambridge, have the same absorbing clarity as his explanations of how Klug and his co-workers created a science of quantitative image analysis in electron microscopy. At once a vade mecum to structural biology and a document of the postwar academic scene in Britain, this book is also quite simply a very good read.’

Stephen Harrison, Harvard University 2017 228 x 152 mm 378pp 60 b/w illus. 13 colour illus.

978-1-107-14737-9 Hardback £29.99 / US$44.99 For all formats available, see

www.cambridge.org/9781107147379

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