About the Book
“Fun, entertaining, witty and darn useful. A magical portal to the big data revolution”
-- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School
“Alex and Gordon’s enthusiasm for Python is contagious"
-- Glenys Thomson, Professor of Integrative Biology, University of California, Berkeley
"A lovely book with humor and perspective"
-- John Novembre, Associate Professor of Human Genetics, University of Chicago
"Python for the Life Sciences is an excellent tutorial"
-- Steven J. Mack, Assistant Scientist, Children's Hospital Oakland Research Institute
If you’re a biologist with little or no experience in programming, but who would like to learn how to write code, Python For The Life Sciences is probably the book you’ve been waiting for!
Python For The Life Sciences is an intuitive and easy-to-follow introduction to computer programming, written specifically for biologists with no computer programming experience.
Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population.
Best of all, we show you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing - a language so versatile and easy to use, that we call it The Swiss Army Knife of Programming Languages.
To get the academic discount for students and teachers, email us at email@example.com using your email account for your accredited school or college, tell us who are and what department you’re in, and we’ll send you a coupon to purchase the book at the current academic price ($30.00).
The authors of this book are both computational biologists and principals at the digital biology consulting firm Amber Biology, based in Cambridge Massachusetts.
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About the Authors
After completing a PhD in biophysics and structural biology at the University of London, Gordon has worked in life science R&D in both Europe and the U.S., with a particular emphasis on molecular engineering and computational biology. In academic and commercial environments ranging from universities and medical schools to small venture capital-funded startups and global pharmaceutical companies, he has served in a diversity of roles from research faculty to company vice president.
Gordon is the author of numerous original scientific articles and patents and has created and managed some very successful research partnerships with industrial, academic and government organizations. He initiated and managed the first translational oncology clinical trial at a multinational pharmaceutical company and has coached and led research project teams in large matrix organizations, as well as large, distributed teams of scientists. software developers and technical specialists, working together across multiple time zones. Gordon’s career path has always reflected his belief that the most interesting and potentially promising areas of research lie at the intersections between the traditional scientific disciplines.
Alex Lancaster is an evolutionary biologist, engineer, writer and consultant. Alex completed his Ph.D. in evolutionary biology at the University of California, Berkeley, and also holds bachelor's degrees in physics and electrical engineering. He has worked in research & development in both Australia and the United States with a major focus on evolutionary and systems biology. He has also worked extensively in genomics, analyzing next-generation sequencing data and has developed tools for clinical and population genomics, with a particular specialization in immunogenetic applications. He has held research and faculty positions in academia, as well as R&D positions in the broadcasting and IT industries.
Alex has published many peer-reviewed papers and is interested in solving problems in biology using evolutionary and complex adaptive systems approaches. He has done pioneering work in this area as a co-developer of the open-source agent-based modeling toolkit, Swarm, one of the first tools for large-scale modeling of collective behavior in biology and beyond. He is passionate about the power of open source and open science approaches to accelerate discovery.
Website: Biosystems Analytics