Python for Bioinformatics (Series in Biomedical Informatics)

by Jason Kinser (Author)

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ISBN-13: 978-0763751869

ISBN-10: 0763751863

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Bioinformatics is a growing field that attracts researchers from many different backgrounds who are unfamiliar with the algorithms commonly used in the field. Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the development of simple programming exercises . Ideal for those with some knowledge of computer programming languages, this book emphasizes Python syntax and methodologies. The text is divided into three complete sections; the first provides an explanation of general Python programming, the second includes a detailed discussion of the Python tools typically used in bioinformatics including clustering, associative memories, and mathematical analysis techniques, and the third section demonstrates how these tools are implemented through numerous applications.

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Editorial Reviews

About the Author

Dr. Kinser has been an associate professor at George Mason University for the past ten years and is currently in the Department of Bioinformatics and Computational Biology. He earned a BA at William Jewell College and as MS at the University of Alabama in Huntsville - both in physics. He also earned a DSc from Southeastern Institute of Technology in optics and electro-optical systems. He has been a guest scientist at the Royal Institute of Technology (KTH) in Stockholm and at the Korea University in Seoul. He also served as an external examiner at the University of Mauritius.

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Product details

Publisher ‏ : ‎ Jones & Bartlett Learning (June 16, 2009)
Language ‏ : ‎ English
Paperback ‏ : ‎ 417 pages
ISBN-10 ‏ : ‎ 0763751863
ISBN-13 ‏ : ‎ 978-0763751869
Item Weight ‏ : ‎ 2.13 pounds
Dimensions ‏ : ‎ 6.9 x 0.9 x 9.9 inches

Best Sellers Rank: #2,623,542 in Books (See Top 100 in Books)
- #654 in Bioinformatics (Books)
- #1,994 in Biochemistry (Books)
- #8,445 in Biology & Life Sciences (Books)

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aloctavodia

Python for FUTURE bioinformatics

Reviewed in the United States on January 28, 2012

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The Author assumes a minimal background in bioinformatics, at least you must know what the field is about, a little of biology and have some ideas of programming (even better if you know Python). You only need to know little high school calculus and some algebra.

The idea of the book is to teach algorithms that are useful for real bioinformatic applications, with the hope that you will be creating you own algorithms or applications in the future. Is not a book to learn BioPython (the preface clearly states that and explains why the skills learned in this book an BioPython could be used in a complementary fashion).

The book uses Python 2, not Python 3. This is not a drawback as some people want to think, Python 2 is going to be the "standard" python for at least few year more and many (but not all) of the features of Python 3 are already present in Python 2.7. Even more important the book relies heavily in the NumPy library (as almost all scientific python programming) and NumPy is not, yet, compatible with Python 3, hence using Python 3 in a book like this will be, at least, non-sense.

The only problem is that sometimes with some topics the author does not take too much time to explain the applications of some ideas, for example in the chapter on Hidden Markov Model (HMM) the Author just explain how to program different HMM implementations. Probably this is a mismatch between my background and the author's (I am closer to the a structural-biologist/biophysics) and some concepts are not used in the exactly same way in different scientific branchs, nothing that not can be solved by reading a Wikipedia entry.

You should buy this book if you want to learn to develop bioinformatics solutions.

3 people found this helpful

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Keith P.

Could be better

Reviewed in the United States on November 19, 2010

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To be honest, I bought this book before I realized that what was out there for bioinformatics. I started a new job, and I knew Python, but I didn't know much about bioinformatics. I was a little disappointed that this book merely references biopython, and doesn't utilize it or show people how to use it. Why not use the tools that are available? In a classroom setting, I guess I can understand why you would want students to learn from the ground up, but this book is essentially teaching people Python in a bioinformatics way. For example, why does the book show how to parse fasta files in Chapter 6. This is merely a lesson in file parsing - something you should know if you understand Python, and why show it if biopython already does this for you.

If you don't know much about Python or Bioinformatics, then this book is probably for you. If you have previous Python experience, I would skip this book.

12 people found this helpful

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Adrian

Solid book but a little dated

Reviewed in the United States on December 11, 2018

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Book hasn't been updated since it has released so it reflects a bunch of Pythonisms that are slightly dated. However, when discussing about bioinformatics content, it's pretty solid. Goes over a lot of the basic ideas and concepts.

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Rocky

Great for learning python and bioinformatics simultaneously

Reviewed in the United States on October 6, 2018

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This book is great if you're just learning python and bioinformatics at the same time. It gives a solid foundation on what each algorithm does so that when you run into a varied version of it, you'll recognize it and know how to use it. Programming background would be helpful but I learned it without much background on programming. The content is very clear and easy to follow.

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carm

Five Stars

Reviewed in the United States on February 17, 2017

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I found it great reading

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A very well done book on implementing algorithms in Python

Reviewed in the United States on December 20, 2009

The author is a well-liked professor at George Mason University, and he has been teaching bioinformatics programming from beginning to advanced for several years. This book is formed somewhat like his lectures for those classes. He assumes you have a background in bioinformatics and that you already know some Python. From there he goes on to show you many of the problems you may be faced with in bioinformatics coded in Python. He actually says that he is trying to answer the question most commonly asked by his students - "How do I put what you just taught into code?".

If you need to a good book on bioinformatics algorithms that is language agnostic may I suggest An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) as well as Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology . The latter book is especially good for computer science students seeking bioinformatics knowledge. Let me also point out that this book is of use for people seeking Python solutions to non-bioinformatics problems. Since much of bioinformatics has to do with dealing with strings, trees, and statistical analysis of data, students of subjects other than biology can find uses for this book.

Do note that the book's one great problem is that it is using Python 2 not Python 3. It is the fault of the designers of Python that most everything written for Python 2 becomes broken in a Python 3 interpreter rather than the fault of this author, yet the problem remains. Fortunately, Python looks enough like pseudocode that you can probably do any translations necessary without too much hair-pulling.

14 people found this helpful

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gani999

Good book, but learn python first.

Reviewed in the United States on September 18, 2009

Python isn't as popular as some other languages amongst bioinformaticans , but it is probably gaining acceptance and this book is a result of it. The author is a practising bioinformatician. This is a good book. It discusses all the mathematical concepts that bioinformaticians usually use, and how they can be implemented in python. It requires, as the author himself says, a fairly good knowledge of mathematics and basic molecular biology. In my opinion, it also requires a good familiarity with the python language. There is a very small introduction to it in the first chapter but beginners will need more exposure to the language than that. Since I can code in python, and I needed a book that jumped straight into the bioinformatics part, I like it.

10 people found this helpful

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Python for Bioinformatics (Series in Biomedical Informatics)

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