Cantitate/Preț
Produs

Computational Thinking for Life Scientists

Autor Benny Chor, Amir Rubinstein
en Limba Engleză Paperback – 7 sep 2022
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.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 23057 lei  3-5 săpt. +1657 lei  6-10 zile
  Cambridge University Press – 7 sep 2022 23057 lei  3-5 săpt. +1657 lei  6-10 zile
Hardback (1) 57158 lei  3-5 săpt.
  Cambridge University Press – 7 sep 2022 57158 lei  3-5 săpt.

Preț: 23057 lei

Nou

Puncte Express: 346

Preț estimativ în valută:
4414 4588$ 3660£

Carte disponibilă

Livrare economică 15-29 ianuarie 25
Livrare express 31 decembrie 24 - 04 ianuarie 25 pentru 2656 lei

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781316647592
ISBN-10: 1316647595
Pagini: 216
Dimensiuni: 169 x 244 x 10 mm
Greutate: 0.43 kg
Ediția:Nouă
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:Cambridge, United Kingdom

Cuprins

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.

Recenzii

'An excellent and very gentle introduction to bioinformatics for biologists. In contrast to books that focus on algorithms and ignore programming or focus on programming without explaining algorithms, this book is a perfect blend of both algorithms and programming!' Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor of Computer Science, University of California at San Diego
'The ability to extract quantitative information from data is an essential skill for the modern biologist. In order to maximize the benefit of programming, use of existing computational tools and effective collaboration with computational scientists, biologists must be able to 'think computationally' by gaining a more algorithmic and logical thinking. In their book, Benny Chor and Amir Rubinstein introduce fundamental computational concepts to life sciences students. Each chapter covers a distinct computational idea motivated by a concrete biological challenge. Questions embedded throughout each chapter and code examples provide hands-on practice. Similarly to the way in which chemistry is perceived as being essential to the biology curriculum, computational thinking should also be considered a part of the modern biologist's basic training. This excellent book is essential reading for undergraduate life sciences students.' Assaf Zaritsky, Ben-Gurion University of the Negev, Israel

Notă biografică


Descriere

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