Quantifying Life: A Symbiosis of Computation, Mathematics, by Dmitry A. Kondrashov PDF

By Dmitry A. Kondrashov

ISBN-10: 022637162X

ISBN-13: 9780226371627

Since the time of Isaac Newton, physicists have used arithmetic to explain the habit of subject of all sizes, from subatomic debris to galaxies. some time past 3 a long time, as advances in molecular biology have produced an avalanche of information, computational and mathematical options have additionally develop into worthy instruments within the arsenal of biologists. yet whereas quantitative ways at the moment are delivering primary insights into organic platforms, the school curriculum for biologists has now not stuck up, and such a lot biology majors are by no means uncovered to the computational and probabilistic mathematical methods that dominate in organic research.

With Quantifying Life, Dmitry A. Kondrashov deals an available creation to the breadth of mathematical modeling utilized in biology this present day. Assuming just a beginning in highschool arithmetic, Quantifying Life takes an cutting edge computational method of constructing mathematical talents and instinct. via classes illustrated with copious examples, mathematical and programming workouts, literature dialogue questions, and computational initiatives of varied levels of trouble, scholars construct and learn types in response to present learn papers and learn how to enforce them within the R programming language. This interaction of mathematical rules, systematically built programming talents, and a vast collection of organic learn themes makes Quantifying Life a useful advisor for professional existence scientists and the subsequent new release of biologists alike.

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Extra resources for Quantifying Life: A Symbiosis of Computation, Mathematics, and Biology

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Instead, premature focus on abstraction obscures the ideas for most students; it is putting the theoretical cart before the experiential horse. I find that students can grasp deep concepts when they are allowed to experience them tangibly as numbers or pictures, and those with an abstract mindset can generalize and add rigor later. As I demonstrate in part 3 of the book, Markov chains can be explained without relying on the machinery of measure theory and stochastic processes, which require graduate-level mathematical skills.

2. 3. 4. 5. 1. 2. 3. analysis of the Jukes-Cantor model IV. Variables that change with time 14. 1. 1. 2. 3. 4. 2. 1. 2. 3. 4. 1. 2. 5. Computational project 15. 1. 1. 2. 3. 2. 1. 2. 3. 3. 1. 2. 4. 1. 2. 5. 1. 2. pharmacokinetics model 16. 1. 2. 1. 2. 3. 4. 1. 2. SIS epidemic model 17. 1. 2. 1. 2. 3. 1. 2. 4. 5. 1. 2. investigation of chaotic dynamics Bibliography Index Preface I wrote this textbook for a course that I developed for first-year college students intending to study biology at the University of Chicago as a part of curriculum reform initiated by the Master of Biological Sciences Collegiate Division José Quintáns.

3. 3. 4. 5. 1. 2. heart rates on two different days 9. 1. 2. 3. 1. 2. 4. 5. Computational projects III. Chains of random variables 10. 1. 2. 1. 2. 3. 4. 5. 1. 2. state strings for a three-state model 11. 1. 1. 2. 3. 2. 3. 4. 1. 2. probability vectors of a three-state model 12. 1. 2. 1. 2. 3. 4. 5. 1. 2. multiple three-state model simulations 13. 1. 2. 1. 2. 3. 4. 3. 4. 1. 2. 3. 4. 5. 1. 2. 3. analysis of the Jukes-Cantor model IV. Variables that change with time 14. 1. 1. 2. 3. 4. 2. 1. 2. 3. 4.

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Quantifying Life: A Symbiosis of Computation, Mathematics, and Biology by Dmitry A. Kondrashov

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