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.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. "A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective"-- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow
"Fun, entertaining, witty and darn useful. Amagical 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
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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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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