Python for the Life Sciences: A Gentle Introduction to Python for Life Scientists
Lancaster, Alexander, Webster, Gordon
Written in a fun, accessible and engaging style, this book will introduce you to the Python language with fully worked examples of Python code drawn from all aspects of life sciences, including bioinformatics, structural biology, developmental biology, and evolutionary biology and ecology.
Using familiar examples designed specifically for life scientists, you'll learn the basics of the language from the very first chapters and progress from there. You'll find out how to use Python to automate lab calculations, search for gene promoter sequences, rotate a molecular bond, build a cellular toggle switch, model animal coat pattern formation, grow a virtual plant, simulate a flu epidemic, or evolve populations.
Python for the Life Sciences provides the tools, confidence and inspiration to start crafting your own Python solutions for the challenges you face in your research. If you are a life scientist interested in learning Python to jump-start your research, this book is for you.
What You'll Learn
- Automate your routine lab calculations with Python
- Find important motifs in genome sequences
- Use object-oriented programming with Python to model the 'flu
- Mine interaction network data for patterns
- Create simulations of biochemical switches
Who This Book Is For
Life and medical scientists with little or no programming experience, and undergraduates, graduate students, postdocs, and professors.
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.
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 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.