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11.E: Genomics and Systems Biology (Exercises) - Biology

11.E: Genomics and Systems Biology (Exercises) - Biology


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These are homework exercises to accompany Nickle and Barrette-Ng's "Online Open Genetics" TextMap. It includes the study of genes, themselves, how they function, interact, and produce the visible and measurable characteristics we see in individuals and populations of species as they change from one generation to the next, over time, and in different environments.

Study Questions

11.1 What are the advantages of high-throughput –omics techniques compared to studying a single gene or protein at a time? What are the disadvantages

11.2 What would the chromatogram from a capillary sequencer look like if you accidentally added only template, primers, polymerase, and fluorescent terminators to the sequencing reaction?

11.3 What are the advantages and disadvantages of clone-by-clone vs. whole genome shotgun sequencing?

11.4 How could you use DNA sequencing to identify new species of marine microorganisms?

11.5 Explain how you could use a microarray to identify wheat genes that have altered expression during drought?

11.6 A microarray identified 100 genes whose transcripts are abundant in tumors, but absent in normal tissues. Do any or all of these transcripts cause cancer? Explain your answer.

11.7 How could you ensure that each spot printed on a microarray contains DNA for only one gene?

11.8 What would the spots look like on a microarray after hybridization, if each spot contained a random mixture of genes?

11.9 What would the spots look like if the hybridization of green and red labeled DNA was done at low stringency?


Cell & Developmental Biology

The CDB emphasis with tracks in Cell & Systems Biology and Medical Biology & Physiology well suited for those interested in basic research, medical and health sciences, and in teaching. Cells are the most basic unit of life. They house DNA, make proteins, produce energy, provide structure, transmit neural information, and sometimes cause disease. The dramatic array of structures and functions that cells perform are enabled by the process of development, which coordinates fundamental and diverse cellular changes and, at the most impressive, produces an entire complex organism like ourselves from one simple starting cell.

Armed with an array of modern methods, including advanced microscopy and powerful genomic approaches, cell and developmental biologists uncover the molecular cues that are responsible for the complex structures within cells, their functions, and the striking changes they undergo during development. The faculty in Cell and Developmental Biology at Berkeley are at the cutting edge of study in a range of important topics including stem cell development, cancer and cellular dysfunction, and understanding of mechanisms that allow cells to divide, move, sense and transmit signals, and regenerate.

Upper Division Requirements

MCB 133L: Cell Biology & Physiology Lab (Fa, Sp 4 un)

OR MCB 170L: Molecular & Cell Biology Laboratory (Su only 4 un)

MCB 133L: Cell Biology & Physiology Lab (Fa, Sp 4 un)

OR MCB 170L: Molecular & Cell Biology Laboratory (Su only 4 un)


Petitioning to Substitute MCB 133L with Research Units

Students may petition to substitute the lab course with equivalent knowledge and units obtained through independent research experience (such as 199 or H196 research), as determined by the Head Faculty Advisor of their major emphasis. Careful consideration and discussion with your faculty advisor are important when making the decision whether to use independent research to substitute the lab, as MCB labs expose students to many biological approaches not always encountered during these research projects. For more information on the approval process see Petition to Substitute MCB Lab Course.

Sample 4-yr Plans

These are just examples, for more sample schedules including spring start and transfer see guide.berkeley.edu or meet with an advisor to explore your options. It is recommended by MCB advisors and faculty to take the upper division lab as early as you can if you are interested in research and/or honors research.

Track 1: Cell & Systems Biology Track 2: Medical Biology and Physiology
Year 1 Year 1
Fall Un Spring Un Fall Un Spring Un
Math 10A 4 Math 10B 4 Math 10A 4 Math 10B 4
Chem 1A/1AL 4 Chem 3A/3AL 5 Chem 1A/1AL 4 Chem 3A/3AL 5
Year 2 Year 2
Fall Un Spring Un Fall Un Spring Un
Chem 3B/3BL 5 Biology 1A/1AL 5 Chem 3B/3BL 5 Biology 1A/1AL 5
Biology 1B 4 Physics 8A 4 Biology 1B 4 Physics 8A 4
Year 3 Year 3
Fall Un Spring Un Fall Un Spring Un
Physics 8B 4 MCB 104 4 Physics 8B 4 MCB 104 4
MCB 102 4 MCB 130 4 MCB 102 4 Elective B 3-4
Year 4 Year 4
Fall Un Spring Un Fall Un Spring Un
MCB 133L 4 Elective A 3-4 Elective B 3-4 MCB 133L 4
Elective A 3-4 MCB 136 4

Approved Electives Lists

CDB Elective List A

CDB Elective LIst B

Molecular and Cell Biology

  • C103 Bacterial Pathogenesis (Sp, 3 units)
  • C112 General Microbiology (F, Su 4 units)
  • C114 Introduction to Comparative Virology (Sp, 4 units)
  • C116 Microbial Diversity (F, 3 units)
  • 132 Biology of Human Cancer (F, 4 units)
  • C134 Chromosome Biology / Cytogenetics (Sp, 3 units)
  • 135A Molecular Endocrinology (F 3 units)
  • 136 Physiology (F, Sp 4 units)
  • 137L Physical Biology of the Cell (Sp, 3 units)
  • 141 Developmental Biology (Sp, 3 units)
  • C148 Microbial Genomics & Genetics (Sp, 4 units)
  • 149 The Human Genome (F, 3 units)
  • 150 Molecular Immunology (F, Sp, 4 units)
  • 153 Molecular Therapeutics (F, 4 units)
  • 160 Cellular and Molecular Neurobiology (F, 4 units)
  • 161 Circuit, Systems and Behavioral Neuroscience (Sp, 4 units)
  • 165 Neurobiology of Disease (Sp, 3 units)
  • 166 Biophysical Neurobiology (F, 3 units)

Molecular and Cell Biology

  • C103 Bacterial Pathogenesis (Sp, 3 units)
  • C112 General Microbiology (F, Su 4 units)
  • C114 Introduction to Comparative Virology (Sp, 4 units)
  • C116 Microbial Diversity (F, 3 units)
  • 130 Cell and Systems Biology (Sp, 4 units)
  • 132 Biology of Human Cancer (F, 4 units)
  • C134 Chromosome Biology / Cytogenetics (Sp, 3 units)
  • 135A Molecular Endocrinology (F 3 units)
  • 137L Physical Biology of the Cell (Sp, 3 units)
  • 141 Developmental Biology (Sp, 3 units)
  • C148 Microbial Genomics & Genetics (Sp, 4 units)
  • 149 The Human Genome (F, 3 units)
  • 150 Molecular Immunology (F, Sp, 4 units)
  • 153 Molecular Therapeutics (F, 4 units)
  • 160 Cellular and Molecular Neurobiology (F, 4 units)
  • 161 Circuit, Systems and Behavioral Neuroscience (Sp, 4 units)
  • 165 Neurobiology of Disease (Sp, 3 units)
  • 166 Biophysical Neurobiology (F, 3 units)

Integrative Biology

  • 103LF Invertebrate Zoology (Sp, 5 units)
  • 104LF Natural History of Vertebrates (Sp, 5 units)
  • 117 & 117LF Medical Ethnobotany with Lab (F, Su, 2 & 2 units)*
  • 123AL Exercise and Environmental Physiology (F, 5 units)
  • 131 General Human Anatomy (F, Su, 3 units)
  • 137 Human Endocrinology (F, 4 units)
  • 140 Biology of Human Reproduction (Sp, 4 units)
  • C143A Biological Clocks: Physiology & Behavior (Alt F, 3 units)
  • C143B Hormones and Behavior (Sp, 3 units)
  • 148 Comparative Animal Physiology (Alt F, 3 units)
  • * both lecture AND lab courses must be taken for IB 117/117L to obtain one elective requirement

Nutritional Sciences & Toxicology

  • 103 Nutrient Function & Metabolism (F, 3 units)
  • 108A Introduction & Application of Food Science (F, 3 units)
  • 110 Toxicology (F, 4 units)
  • 160 M etabolic Bases of Human Health and Disease s (Sp 4 units)
  • 161A Medical Nutrition Therapy I (F 4 units)

Plant & Microbial Biology

  • 135 Physiology & Biochemistry of Plants (F 3 units)
  • 150 Plant Cell Biology (F 3 units)
  • 160 Plant Molecular Genetics (Sp 3 units)
  • 110 Introduction to Biological Psychology (F, Sp, Su 3 units)
  • C113 Biological Clocks: Physiology & Behavior (Alt F 3 units)
  • C116 Hormones & Behavior (Sp 3 units)

Public Health

  • 141 Intro to Biostatistics (Su 5 units)
  • 142 Intro to Probability & Statistics in Bio & Public Health (F,Sp 4 units) - Note: For students who have completed Math 10A/B, or Stat 2 or 20, this course is not accepted to meet the elective requirement.
  • 150B Intro to Environmental Health Sciences (F 3 units)
  • 162A Public Health Microbiology (F, Su 4 units)

Approved Courses but NOT Regularly Offered

  • MCB 113 Applied Microbiology & Biochemistry
  • MCB 115 Molecular Biology of Animal Virus
  • MCB 137 Computer Simulation in Biology (replaced by MCB 137L)
  • MCB 143 Evolution of Genomes, Cells & Development (F, 3 units)
  • MCB 163 Mammalian Neuroanatomy
  • MCB 167 Physiological & Genetic Basis of Behavior
  • MCB C145 Genomics
  • MCB C146 Topics in Computational Biology and Genomics
  • NSTX 150 Mechanics of Metabolic Regulation
  • PH 150A Intro to Epidemiology & Human Disease

Reserve Mandir

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Integer Linear Programming in Computational and Systems Biology

This book has been cited by the following publications. This list is generated based on data provided by CrossRef.
  • Publisher: Cambridge University Press
  • Online publication date: May 2019
  • Print publication year: 2019
  • Online ISBN: 9781108377737
  • DOI: https://doi.org/10.1017/9781108377737
  • Subjects: Genomics, Bioinformatics and Systems Biology, Life Sciences, Computer Science, Computational Biology and Bioinformatics

Email your librarian or administrator to recommend adding this book to your organisation's collection.

Book description

Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists know about it. This how-to and why-do text introduces ILP through the lens of computational and systems biology. It uses in-depth examples from genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more, to establish the power of ILP. This book aims to teach the logic of modeling and solving problems with ILP, and to teach the practical 'work flow' involved in using ILP in biology. Written for a wide audience, with no biological or computational prerequisites, this book is appropriate for entry-level and advanced courses aimed at biological and computational students, and as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.

Reviews

'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.'


Genomics and the 4 M framework

Two aspects distinguish data science in the natural sciences from social science context. First, in the natural sciences much of the data are quantitative and structured they often derive from sensor readings from experimental systems and observations under well-controlled conditions. In contrast, data in the social sciences are more frequently unstructured and derived from more subjective observations (e.g., interviews and surveys). Second, the natural sciences also have underlying chemical, physical, and biological models that are often highly mathematized and predictive.

Consequently, data science mining in the natural sciences is intimately associated with mathematical modeling. One succinct way of understanding this relationship is the 4 M framework, developed by Lauffenburger [39]. This concept describes the overall process in systems biology, closely related to genomics, in terms of (i) Measuring the quantity, (ii) large-scale Mining, which is what we often think of as data science, (3) Modeling the mined observations, and finally (4) Manipulating or testing this model to ensure it is accurate.

The hybrid approach of combining data mining and biophysical modeling is a reasonable way forward for genomics (Fig. 1b). Integrating physical–chemical mechanisms into machine learning provides valuable interpretability, boosts the data-efficiency in learning (e.g., through training-set augmentation and informative priors) and allows data extrapolation when observations are expensive or impossible [40]. On the other hand, data mining is able to accurately estimate model parameters, replace some complex parts of the models where theories are weak, and emulate some physical models for computational efficiency [41].

Short-term weather forecasting as an exemplar of this hybrid approach is perhaps what genomics is striving for. For this discipline, predictions are based on sensor data from around the globe and then fused with physical models. Weather forecasting was, in fact, one of the first applications of large-scale computing in the 1950s [42, 43]. However, it was an abject flop, trying to predict the weather solely based on physical models. Predictions were quickly found to only be correct for a short time, mostly because of the importance of the initial conditions. That imperfect attempt contributed to the development of the fields of nonlinear dynamics and chaos, and to the coining of the term “butterfly effect” [43]. However, subsequent years dramatically transformed weather prediction into a great success story, thanks to integrating physically based models with large datasets measured by satellites, weather balloons, and other sensors [43]. Moreover, the public’s appreciation for the probabilistic aspects of a weather forecast (i.e., people readily dress appropriately based on a chance of rain) foreshadows how it might respond to probabilistic “health forecasts” based on genomics.


Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses

Background: Endurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise. For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition.

Results: We obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways. Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels. In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition.

Conclusions: To the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

Keywords: Endurance exercise Horse Metabolome Multiple factor analysis Regulome Systems biology Transcriptome miRNome.

Figures

Metabolic regulation in the cell…

Metabolic regulation in the cell after endurance exercise. Endurance exercise increased the production…

Regulatory network linking metabolites, metabolic…

Regulatory network linking metabolites, metabolic genes and miRNAs. We identified a total of…

Activators and repressors of the…

Activators and repressors of the regulatory network. a The regulatory network was driven…

Multiple factor analysis projection plot…

Multiple factor analysis projection plot at T0 in an independent cohort of 13…

Multiple factor analysis projection plot…

Multiple factor analysis projection plot at T1 in an independent cohort of 31…

A model for increased intestinal…

A model for increased intestinal permeability after exercise based on coordinated metabolite and…


Bioinformatics Exercises

Download proteome of Halobacterium spec. with wget and look at it:

a) How many predicted proteins are there?

b) How many proteins contain the pattern “WxHxxH” or “WxHxxHH”?

c) Use the find function (/) in ‘less’ to fish out the protein IDs containing the pattern or more elegantly do it with awk:

a) Generate list of sequence IDs for the above pattern match result

(i.e. retrieve my_IDs from step 2c). Alternatively, download the pre-generated file with wget.

5. Looking at several different patterns:

a) Generate several lists of sequence IDs from various pattern match results (i.e. retriev

e a.my_ids , b.my_ids , and c.my_ids from step 2c).

b) Retrieve the sequences in one step using the fastacmd in a for-loop: 6. Run blastall with a few proteins in myseq.fasta against your newly created Halobacterium proteome database. Create first a complete blast output file including alignments. In a second step use the ‘m -8’ option to obtain a tabular output (i.e. tab separated values).

The filed descriptions of the Blast tabular output (from the “-m 8” option) are available here.


Biology Department

Biology has had decades of extraordinary leadership which has served it well and has resulted in the design of holistic programs to prepare students for post baccalaureate studies, health professions, science education, and other science-related careers. The mission of the Biology Department is in consonance with the mission and goals of the University, especially as it relates to the development of tomorrow's leaders in professions utilizing biological knowledge. The major provides instruction in fundamental biological concepts, immersion in hands-on, minds-on field and laboratory exercises, and opportunities for greater specialization in emerging fields like biophysics, computational biology and genomics. Critical reasoning, intellectual inquiry, and mastery of the scientific jargon are aggressively fostered in the biology program. From the very beginning, students are involved in the practice of scientific inquiry and, in advanced courses, motivated to formulate testable hypotheses, design experiments and analyze data. These competencies are then demonstrated in the BIOL capstone course, BIOL401 Senior Seminar, in which students deliver a high quality scientific presentation and field questions which may be posed by any member of the BIOL faculty. The program promotes leadership and collaborative skills through group projects including recitations/precepts, discussions, lab experiments and reports. Advanced undergraduate students may serve as teaching and laboratory assistants. The department supports a chapter of Beta Kappa Chi, The Biology Club, and Pre-Professional Health Careers Advisory Program. These student-centered organizations offer leadership and service opportunities.

Vision Statement

The biology major is designed to: give students a broad understanding of the processes, concepts, and structures that characterize life at three basic levels: molecular/cellular, system/organism, and community/ecosystem encourage scientific investigation and experimentation through laboratory and field experiences and independent, authentic research and finally, prepare students for the further pursuit of graduate or professional school, or for careers in health care, public and private research, teaching, and related fields.

DEGREE PROGRAMS

The biology core curriculum requires the completion of two mandatory introductory courses (cr. hr = 8) within the first year, after which students may select 5 to 7 advanced biological courses (cr. hr = 19 - 28) based on interests and career goals with the restriction that at least one course is taken in each of three major categories of biology (i.e., organismal/physiology, cellular and molecular, and environmental/ecology /evolution).

1. A required "core" of nine biology courses with labs representing three levels of life processes:

  • three introductory courses with labs (BIOL120/121, BIOL230/231)
  • molecular & cell biology (BIOL250/251)
  • five biology electives with advanced content in each of the three levels

2. Senior seminar
3. Four required courses in chemistry
4. Two required courses in math
5. Two required courses in physics

Graduate Study in Biology

The graduate study program in biology leads to the Master of Science degree. The offering of a graduate degree in biology has several purposes. One of these is to offer students who have attained the baccalaureate degree in biology or other natural sciences the opportunity to broaden and increase their knowledge in the biological sciences. Another is the opportunity for students to enter into or expand their experience in the area of experimental research in biology. These objectives may be achieved through selection of elective courses offered in this department and allied areas (chemistry, agriculture, veterinary medicine, etc.), and by the selection of a research area of concentration. The latter is with the assistance of a major advisor in the department who will usually act as the student's major professor. All graduate students are required to teach for one (1) year in the Freshman Biology Program.

M.S. in Biology

The biology graduate program is designed to prepare students for further graduate work leading to a Ph.D. to provide professional biologists with advanced research and educational opportunities and to provide students with a broad-based graduate program allowing for specialization in the diverse fields of inquiry represented by the faculty of the department. The application procedure is simple!

Ph.D. in Integrative Biosciences

Advances in the life sciences that address local and global challenges require new approaches to graduate education and research. The Tuskegee University Integrative Biosciences (IBS) Ph.D. program is designed to develop professionals who have not only technical proficiency but who also possess the flexibility and adaptability to address the complexities of current challenges. Read about our mission, vision and collaborators of this program.

PROFESSIONAL DEVELOPMENT

The Learning Resource Center (LRC), located in room 207 Armstrong Hall, contains a library of information about medical schools and their curricula, admissions requirements, and financial planning that can be accessed for reference by any student (Biology or non-Biology major). Similar information is available about other programs such as Dentistry, Optometry, Pharmacy, Physical Therapy, Physician's Assistant, and Public Health. The Center also contains printed and computerized information about MCAT, GRE, and other standardized examinations as well as information on summer enrichment/research programs and post baccalaureate programs. Applications for these examinations and programs are available in the Center.

PRE-PROFESSIONAL HEALTH CAREERS ADVISORY PROGRAM

The Pre-Professional Health Careers Advisory Program (PHCAP) was established to assist student in the applications process for health careers. There are a series of workshops, meetings and private sessions that will ensure that each student has a well-rounded application.

MEMORANDUMS OF UNDERSTANDING (MOUs)

The Tuskegee University College of Arts and Sciences has partnerships with various medical institutions around the country with Early Acceptance Programs.

OFFICE OF UNDERGRADUATE RESEARCH

The Office of Undergraduate Research (OUR) is focused on exposing student to research-based careers and internships. Several seminars are hosted to allow for student to have one-on-on contact with working professional and laboratory techniques that will make them successful in the future.

Research Careers Program is coordinated by Dr. Marcia Martinez. The purpose of the program is to assist faculty engaged in biomedical research at Tuskegee University with the development of competitive research programs, as well as increase the number of underrepresented minorities at Tuskegee University conducting biomedical research. The program was establish to increase access research laboratories, attend national scientific meetings, establish biomedical seminars for faculty and students, and promote student research through mentoring. Students enrolled in undergraduate research can gain experience from faculty members in Biology or from other biomedical departments on campus. Some of the research conducted on campus has emphasis in cancer, toxicology, or reproductive physiology.

The MICROBE Project aims to enhance the exposure of undergraduate students to research in and outside of the lecture hall. This Undergraduate Research program seeks to provide more opportunities for students to perform research during the academic year.


Reviews & endorsements

'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

'Sneppen has written a wonderfully friendly and readable book on the principles of biological cells for physicists. He presents concepts and models at a level that is sufficiently deep to convey powerful insights, while keeping the math to the absolutely minimal level that is needed to be clear and informative. This book is pioneering in covering scientific terrain that is largely not covered much elsewhere, but will be in the future - including feedback, regulation, networks, bistability in the lambda-phage switch, DNA looping, diffusion in cells, epigenetic regulation and cellular evolution. I highly recommend it as a deeply insightful book about the principles of biology and a great read.' Ken Dill, Laufer Center, Stony Brook University


Reviews & endorsements

'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

'Sneppen has written a wonderfully friendly and readable book on the principles of biological cells for physicists. He presents concepts and models at a level that is sufficiently deep to convey powerful insights, while keeping the math to the absolutely minimal level that is needed to be clear and informative. This book is pioneering in covering scientific terrain that is largely not covered much elsewhere, but will be in the future - including feedback, regulation, networks, bistability in the lambda-phage switch, DNA looping, diffusion in cells, epigenetic regulation and cellular evolution. I highly recommend it as a deeply insightful book about the principles of biology and a great read.' Ken Dill, Laufer Center, Stony Brook University