Listen to, or read a transcript of, a podcast interviewwith Biosystems Analytics’ and Python for the Life Sciences co-author, Alex Lancaster. The interview was recorded for our digital publisher Leanpub’s author podcast series, by Leanpub co-founder Len Epp. In a wide-ranging discussing Len discussed Alex’s career, funding in science, evolutionary biology, the state of the book publishing industry and many other things. The podcast was recorded back in November 2016.
I’m happy to announce that if you live in the Greater Boston area that our book, Python For The Life Sciences is now on a book shelf near you. You can pick up a copy at Harvard Book Store in Harvard Square, Cambridge, Porter Square Books in, you guessed it, Porter Square, Cambridge or The Book Rack in Arlington. We hope to continue to add more bookstores.
The book has ended up somewhat larger than originally planned, clocking in at over 300 pages, and covers a wide range of life science research topics from biochemistry and gene sequencing, to molecular mechanics and agent-based models of complex systems. We hope that there’s something in it for anybody who’s a life scientist with little or no computer programming experience, but who would love to learn to code.
You can download the complete first chapter for free at Leanpub and everybody who buys this first edition will have complete access to book updates to this particular edition. Help us improve the book by emailing us feedback or if you spot any errors to: firstname.lastname@example.org
Our Amber Biology book Python For The Life Sciences is now nearing publication – we anticipate sometime in the early summer of 2016 for the publication date. As requested by many folks we are releasing the first draft of the table of contents. If you’re interested in updates you can sign up for our book mailing list. You can also checkout a preview chapter on Leanpub.
Python at the bench:
In which we introduce some Python fundamentals and show you how to ditch those calculators and spreadsheets and let Python relieve the drudgery of basic lab calculations (freeing up more valuable time to drink coffee and play Minecraft)
Building biological sequences:
In which we introduce basic Python string and character handling and demonstrate Python’s innate awesomeness for handling nucleic acid and protein sequences.
Of biomarkers and Bayes:
In which we discuss Bayes’ Theorem and implement it in Python, illustrating in the…
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My Amber Biology colleague, Gordon Webster, and I are working on an accessible introduction for biologists interested in getting into programming. Python for the Life Scientists will cover an array of topics to introduce Python and also serve as inspiration for your own research projects.
But we’d also like to hear from you.
What are the life science research problems that you would tackle computationally, if you were able to use code?
You can contact us here in the comments, on email@example.com or on the more detailed post: