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License: MIT License
Bioinformatics and Computational Biology with Python
License: MIT License
BICBpy - Bioinformatincs and Computational Biology Tutorial with Python Authors: Moritz Beber, Nikolaus Sonnenschein, and Marc-Thorsten Hütt Jacobs University Bremen, Germany Purpose: - Undergrad teaching - Python fundamentals and standard library (urllib2, pickle) - Biopython: Genomic sequences - NetworkX: Moritz? - Numpy and Scipy: Solving ODEs Tutorials: 1. General introduction (using IPython + a Beamer) 1.1 Python? 1.2 IPython shell 1.3 Neat example 1.4 Syntax 1.4.1 Indentation 1.4.2 Assignments 1.4.3 Functions 1.4.4 Control structures 1.5 Everything is an object ... 1.5.1 Introspection 1.6. Solve as many python riddles as you can (www.pythonchallenge.com) 2. Working with sequences 2.1 Read in a genomic nucleotide sequence from a fasta/genbank file (see alo SeqIO.read and SeqIO.parse) 2.2 Determine the GC content (G+CA+T+G+CÂ100 ) of the sequence (see Seq.count) 2.3 Determine all tetranucleotide frequencies of the sequence (a python dictionary maybe useful) and plot them (see list_plot) 2.4 Read in another genomic sequence and compare it to the previous sequence using both GC content and tetranucleotide frequencies (see scatter_plot and pearsonr) 2.5 Read in the E. coli, Marinobacter aquaeoli and S. aureus sequences and determine their tetranucleotide frequency profiles 2.6 Use these profiles to predict the origin of the anonymous sequence chunks contained in the random_chunks.fasta file. They all have been obtained from either of the previously mentioned genomes. 3. NetworkX + GraphTheory + Protein-Protein interaction networks 4. ODEs Installation: Resources: Biopython documentation http://www.biopython.org/wiki/Documentation NetworkX documentation http://networkx.lanl.gov/contents.html References: [1] http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient Reading Material: Bassi S, 2007 A Primer on Python for Life Science Researchers. PLoS Comput Biol 3(11): e199. doi:10.1371/journal.pcbi.0030199 Code Like a Pythonista: Idiomatic Python http://python.net/%7Egoodger/projects/pycon/2007/idiomatic/handout.html
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