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.
Big Data has become an increasingly large presence in the life science R&D world, but as I have blogged about previously, increasingly larger datasets and better machine algorithms alone, will not leverage that data into bankable knowledge and can lead to erroneous inferences. My Amber Biology colleague, Gordon Webster has a great post over on LinkedIn leavening the hype around Big Data, pointing out that analytics and visualizations alone are insufficient for making progress in extracting knowledge from biological datasets:
Applying the standard pantheon of data analytics and data visualization techniques to large biological datasets, and expecting to draw some meaningful biological insight from this approach, is like expecting to learn about the life of an Egyptian pharaoh by excavating his tomb with a bulldozer
“-omics” such as those produced by transcriptomic and proteomic analyses are ultimately generated by dynamic processes consisting of individual genes, proteins and other molecules…
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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: