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Python for Bioinformatics
Author: Jason KinserOVERVIEW
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.
TABLE OF CONTENTS
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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