Computational Thinking for Life Scientists

Introduces fundamental computational ideas and concepts in a biological context, with real-world examples and exercises in Python.

Benny Chor (Author), Amir Rubinstein (Author)

9781107197244, Cambridge University Press

Hardback, published 8 September 2022

216 pages
25 x 17.5 x 1.5 cm, 0.56 kg

'… an excellent introduction to programming for scholars in the life sciences … This book provides a strong, domain-specific foundation and belongs in the library of any institution supporting instruction in the life sciences. … Highly recommended.' J. Forrest, Choice

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.

Introduction
Part I. Programming in Python: 1. Crash introduction to python
2. Efficiency matters – gentle intro to complexity
Part II. Sequences: 3. Sets dictionaries and hashing
4. Regular expressions and biological patterns
Part III. Networks: 5. Basic notions in graph theory
6. Shortest paths and breadth first search
7. Simulation of regulatory networks
Part IV. Images: 8. Digital images representation
9. Image processing
Part V. Limitations of Computing: 10. Mission impossible
11. Mission infeasible
Index.

Subject Areas: Genetics [non-medical PSAK]