Python for the Life Sciences: A Gentle Introduction to Python for Life Scientists

Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research.

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, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you.

What You'll Learn

• Write Python scripts to automate your lab calculations
• Search for important motifs in genome sequences
• Use object-oriented programming with Python
• Study mining interaction network data for patterns
• Review dynamic modeling of biochemical switches

Who This Book Is For

Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers.

About the Authors

Alexander Lancaster is a Research Scholar at the Ronin Institute, a visiting scholar at the University of Sydney, and a Partner at Amber Biology, a digital biology research firm in Cambridge, Massachusetts. Alex holds a PhD in evolutionary biology at the University of California, Berkeley, and degrees in physics and engineering. He has worked in R&D in Australia, the United Kingdom and the United States with a major focus on evolutionary and systems biology. He has also worked extensively in the fields of artificial life, complex systems, computational biology and genomics. He has held research and faculty positions as well as R&D positions in the IT industries.

Alex has published many peer-reviewed papers and was 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.

Gordon Webster has a PhD in biophysics and structural biology from 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 faculty to vice president.

Gordon is the author of numerous original scientific articles and patents and has created and managed 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, distributed teams of scientists. software developers and technical specialists. 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.