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Python for Bioinformatics

Author(s): Jason Kinser, DSc, George Mason University
Details:
  • ISBN-13: 9780763751869
  • ISBN-10:0763751863
  • Paperback    417 pages      © 2009
Price: International Sales $86.95 US List
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Overview

Part of the JONES AND BARTLETT SERIES IN BIOMEDICAL INFORMATICS

Bioinformatics is a growing field that attracts researchers from many different backgrounds, including some who are unfamiliar with 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 the upper-level undergraduate and graduate courses, as well as those hoping to expand their knowledge of programming for bioinformatics, Kinser's text emphasizes the proper 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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Click here for python codes and data files to accompany Python for Bioinformatics 

Interested in becoming a Biomedical Informatics Series author?  Click HERE to learn more!

ShowKey Features

A flexible design allows individuals to pick and choose special topics of interest to meet specific course needs.

The programs provided in the text replicate current research in bioinformatics.

Includes numerous real-world application and examples throughout.

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ShowTable of Contents

1.   Introduction
2.   NumPy and SciPy
3.   Image Manipulation
4.   Akando and Dancer Modules
5.   Statistics
6.   Parsing DNA Data Files
7.   Sequence Alignment
8.   Dynamic Programming
9.  Tandem Repeats
10. Hidden Markov Models
11. Genetic Algorithms
12. Multiple Sequence Alignment
13. Gapped Alignments
14. Trees
15. Text Mining
16. Complexity
17. Clustering
18. Self-Organizing Maps
19. Principals
20. Species Identification
21. Fourier Transforms and Correlations
22. Correlations
23. Numerical Sequence Alignment
24. Gene Expression Array Files
25. Spot Finding and Measurement
26. Spreadsheet Arrays and Displaying the Data
27. Applications with Expression Arrays


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ShowAbout the Author(s)

Jason Kinser, DSc-George Mason University

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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ShowAppropriate Courses

Intended for upper-level undergraduate and graduate courses within the departments of Bioinformatics and Computation Biology.

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