A F I R S T COUR S E IN
SYSTEMS BIOLOGY
SOLUTIONS TO EXERCISES THIRD EDITION
Eberhard O. Voit, Melissa K. Kemp, Po-Wei Chen, I-Chun Chou, Sepideh Dolatshahi, Luis Fonseca, James Kelvin, Yun Lee, Zhen Qi, Andrew Sedler, and Weiwei Yin
Atlanta & Dallas, 2024
PREAMBLE TO SOLUTIONS Most exercises in A First Course in Systems Biology are structured to be open-ended and stimulate self-motivated learning and exploration. As a consequence, they do not have unique solutions. Some students find this ambiguity uncomfortable and would much rather be assured that there is one correct solution. However, after a while, they often see that open-ended questions are much closer to reality, especially with respect to complex phenomena in biology. Furthermore, the students recognize that they can structure their solutions, to some degree, according to their own preference: some students like conceptual approaches, others like simulations, yet others are intrigued by rigorous proofs. Some enjoy trying out multiple changes in model settings and studying the responses of a system; others would much rather extract the essence of a problem and try to solve it as concisely as possible, while some prefer to spend their time screening the literature for experts’ answers or solutions to similar problems. Many students have asked us: how many simulations do I have to do? Initially, they sometimes do not like my answer: “Before you execute a simulation, make a prediction of what you expect to happen. If your predictions are consistently correct, at least qualitatively, you may stop. However, if your predictions are sometimes correct and sometimes false, there are aspects of the system you don’t really understand. You need to keep on simulating, analyzing, and interpreting.” Many exercises permit a lot of latitude in terms of breadth and depth, and the instructor might want to specify the expected length of a report, the level of detail of an analysis, and possibly a specific focus. For instance, if students are asked to explore different visualizations of protein structures in the protein data bank PDB, one could ask them to focus on specific proteins that, for some reason, are of particular interest to the student, class, or the program. Some exercises ask for reports excerpting information from the literature or the Internet. The answers proposed here usually do not offer as much detail as one might expect from a student, but merely point to relevant information and highlight important topics. The instructor also needs to decide how to handle the issue of artificial intelligence as a tool for generating solutions. Similarly, the exploration of software requires working hands-on with the program, and the solutions just provide pointers as to where and how to start. Again, it might be useful to connect these software questions with a specific biological question. The total number of exercises per chapter is probably too high for a typical onesemester class but affords the instructor some flexibility in choosing exercises that are deemed most relevant for the types of students taking the class, their backgrounds in biology, mathematics, and computing, and the department or program in which the course is taught. Finally, the large number and variety of exercises, and the in-built flexibility in solution strategies, suggest that some of the proposed solutions could probably be improved. We would be very happy to receive better solutions and possibly include them in future versions of this solution manual.
SOLUTIONS TO EXERCISES IN CHAPTER 1 1.1. Search the Internet, as well as different dictionaries, for definitions of a “system.” Extract commonalities among these definitions and formulate your own definition. Solution: A good start is an Internet search with “definition of system” as the search term, which leads to a lot of hits. There is a huge literature about systems, and philosophers have considered the concept even before Aristotle and Plato. The definitions of the term are of course all slightly different, but many of them have some key features in common. According to these commonalities: A system is a group, assemblage, or organized set of several or many parts, elements, objects, or items. The parts are interconnected or interrelated; they regularly interact. The parts and their interconnections create a unified or integrated whole that has defined boundaries; everything outside the boundaries is considered as the environment. The interconnections within the system create some functionality. The functionality is complex and sometimes emergent, which means that it cannot be identified in the components alone. Systems have structure and behavior. Many systems have internal regulators. Open systems process input and/or generate output; closed systems do not exchange mass or energy with the environment. Terms sometimes seen as synonyms (at least of some systems) are “network,” “scheme,” “complex of methods,” and “set of rules.” The word “system” comes from Greek and refers to a composition or combined setup of several parts. 1.2. Search the Internet for definitions of “systems biology.” Extract commonalities among these definitions and formulate your own definition. Solution: The term “systems biology” is roughly synonymous with “analysis of biological systems.” Thus, the concept and definition of “systems biology” share much with the generic definitions of systems in Exercise 1.1 but are specifically applied to biology. A genuine aspect of systems biology is that it is often contrasted to reductionism, that is, the philosophy, especially in biology, of taking things further and further apart in order to study the properties of the ultimate components. While systems biology aims to reconstruct systems from components, the dichotomy between systems biology and reductionism should not be seen as a
competition of what is right and what not, because systems biology would not be able to function without targeted reductionistic research. At the same time, only knowing the components is insufficient and requires a complementary phase of reconstruction. Other genuine features of system biology include the fact that biological systems naturally span multiple organizational, spatial, and temporal scales, which are to be integrated into comprehensive systems studies to explain overall function. Also, the aspect of emerging properties is usually associated with biological systems. Finally, systems biology is very interested in dynamics, and some definitions of systems biology declare it as the application of dynamical systems theory to biological phenomena. While some authors define systems biology as an extension of molecular and -omics biology, one should keep in mind that physiology and ecology have been practicing systems analysis in biology for a long time and that fields like cybernetics and biomathematics could also be seen as its precursors. Ultimately, as the text explains, systems biology is really the result of the confluence of many fields, and this fact should enter its definition. 1.3. List ten systems within the human body. Solution: Obvious examples include: the nervous system; the gastrointestinal system; and the cardiovascular systems. However, the human body is full of uncounted “smaller” or less prominent systems, such as: the system with which the eye responds to light; the system in which neurotransmitters are passed through different brain sections; the uptake system with which cells incorporate materials or signals; a large number of specific metabolic pathway systems; the system of the ribosome that translates mRNA into proteins; the many gene regulatory systems that respond to specific situations or demands; and the information system within the genetic code. 1.4. Exactly what features make the system in Figure 1.10 so much more complicated than the system in Figure 1.8? Solution: The main reason that the system in Figure 1.8 is so much easier to understand than the system in Figure 1.10 is its linear structure. Our intuition is