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Bioinformatics Programming Using Python: Practical Programming for Biological Data [Paperback]

Mitchell L. Model
4.5 out of 5 stars  See all reviews (6 customer reviews)

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Book Description

December 25, 2009 059615450X 978-0596154509 1st

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming.

Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.

  • Become familiar with Python's fundamentals, including ways to develop simple applications
  • Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access
  • Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics
  • Learn how to apply the principles and techniques of object-oriented programming
  • Benefit from the "tips and traps" section in each chapter

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Bioinformatics Programming Using Python: Practical Programming for Biological Data + Practical Computing for Biologists
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Editorial Reviews

Book Description

Practical Programming for Biological Data

About the Author

Mitchell L. Model has worked in a wide range of platforms, languages, technologies and domains. For much of his career he has been an independent consultant, providing training, mentoring, tools, and support to software development groups learning to use new technologies and practices. During the past 15 years his work has focused on bioinformatics.


Product Details

  • Paperback: 528 pages
  • Publisher: O'Reilly Media; 1st edition (December 25, 2009)
  • Language: English
  • ISBN-10: 059615450X
  • ISBN-13: 978-0596154509
  • Product Dimensions: 9.1 x 7 x 1 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Best Sellers Rank: #365,215 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews
29 of 31 people found the following review helpful
By C. Chin
Format:Paperback
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.
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19 of 20 people found the following review helpful
2.0 out of 5 stars Not ready for use as an undergrad txt, IMO November 1, 2012
Format:Paperback
I've been using O'Reilly's "Tisdall's Beginning Perl for Bioinformaticsl" to introduce my junior/senior biology students in to programming, but recently looked to this text as a possibly alternative. My hope with that Python's simpler syntax might make it easier for students to learn. I examined the first 3 chapters.

Unfortunately, I found this book to be inferior for such a purpose. The largest drawback was that many of the sample pieces of code did not actually execute, because they had dependencies on other pieces of code which, while discussed in the text, were not explicitly imported when the code is run. The fact that the examples did not import these methods them makes if very laborious for the reader to "run/execute/test" code as they work through the examples as suggested.

A second drawback is that the text is basically a programming book with a set biological examples; biologists, in my opinion are better served showing them what the language can do for them as soon as possible. I have found that the narrative voice used in other O'Reilly Bioinfo guides to be more to this standard and thus better able to promote student learning.

Unfortunately I shall stick with Tisdall's Beginning Perl for Bioinformatics, at least until a text becomes available which better addresses these limitations.
Hope this review is helpful.
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13 of 14 people found the following review helpful
5.0 out of 5 stars A very good Book..!! January 5, 2010
Format:Paperback
This book is really a great one for Bioinformatics programming. It is very easy to understand and very good examples are given in the book that are related to biological data. The content of the book is very well organized. All the topics are very well covered and explained. The biggest plus point of this book is that examples and data are picked very wisely which is really needed for Bioinformatics readers to understand well and to make their learning process easy and interesting. All the tables and examples, errors one might get while programming, screen shots of data extraction from database are very good and logical. I am sure this book will be admired by all biologists who want to learn Python and those who are familiar with Python and looking for a book to enhance their programing skills for querying Databases, extracting data from HTML, working with XML, URLs, OOL etc, This is the best book as it has covered everything with every single detail with an ease to understand the content. I Think this book will make Bioinformatics programmers life easier..!!
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