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Highlights
HIGHLIGHT
HIGHLIGHT
Textbook
TEXTBOOK
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 2016 246 x 189 mm 425pp 124 b/w illus. 978-1-107-07429-3 Hardback £99.99 / US$175.00 978-1-107-42488-3 Paperback £39.99 / US$64.99 For all formats available, see
www.cambridge.org/9781107074293
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