Bioinformatics Programming Using Python_ Practical Programming for Biological Data (Animal Guide)
|Автор:||@petabyte (Science and technology)|
|Дата создания:||05.05.2020 11:01|
|Описание:||'Comparing to Perl, Python has a quite lagged adoption as the scripting language of choice in the field of bioinformatics, although it is getting some moment recently. If you read job descriptions for bioinformatics engineer or scientist positions a few year back, you barely saw Python mentioned, even as "nice to have optional skill". One of the reasons is probably lacking of good introductory level bioinformatics books in Python so there are, in general, less people thinking Python as a good choice for bioinformatics. The book "Beginning Perl for Bioinformatics" from O Reilly was published in 2001. Almost one decade later, we finally get the book "Bioinformatics Programming Using Python" from Mitchell Model to fill the gap. When I first skimmed the book "Bioinformatics Programming Using Python", I got the impression that this book was more like "learning python using bioinformatics as examples" and felt a little bit disappointed as I was hoping for more advanced content. However, once I went through the book, reading the preface and everything else chapter by chapter, I understood the main target audiences that author had in mind and I thought the author did a great job in fulfilling the main purpose. In modern biological research, scientists can easily generate large amount of data where Excel spreadsheets that most bench scientists use to process limiting amount of data is no longer an option. I personally believe that the new generation of biologists will have to learn how to process and manage large amount inhomogeneous data to make new discovery out of it. This requires general computational skill beyond just knowing how to use some special purpose applications that some software vendor can provide. The book gives good introduction about practical computational skills using Python to process bioinformatics data. The book is very well organized for a newbie who just wants to start to process the raw data their own and get into a process of learning-by-doing to become a Python programmer. Th|
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