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About the Book

Many life science researchers are missing out on some of the wonderful computational tools that are out there, and that could be invaluable in helping them to manage and analyze their laboratory data. This may be due to a lack of awareness that these tools exist and that many of them are inexpensive or free, or it may be out of fear that learning to use them will take too much time out of an already hectic schedule. This brief Python code tutorial for life science computing, aims to point life scientists with relatively little exposure to programming languages, in the right direction to be able to start using the Python programming language to write useful code that can solve real problems in their work and their research.


About the Author

Gordon Webster’s avatar Gordon Webster

@gwebster

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.

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