Download free course Biopython: Tutorial and Cookbook, pdf file on 360 pages by by Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich, Bartek Wilczy?ski.
The Biopython Project is an international association of developers tools for computational molecular biology. Python is an object oriented, interpreted,flexible language that is becoming increasingly popular for scientific computing. Python is easy to learn, hasa very clear syntax and can easily be extended with modules written in C, C++ or FORTRAN.
Thegoal of Biopython is to make it as easy as possible to use Python for bioinformatics by creating high-quality, reusable modules and classes.
Biopython features include parsers for various Bioinformatics file formats (BLAST, Clustalw, FASTA, Genbank,...), access to online services (NCBI, Expasy,...), interfaces to commonand not-so-common programs (Clustalw, DSSP, MSMS...), a standard sequence class, various clusteringmodules, a KD tree data structure etc.
Thegoal of Biopython is to make it as easy as possible to use Python for bioinformatics by creating high-quality, reusable modules and classes.
Biopython features include parsers for various Bioinformatics file formats (BLAST, Clustalw, FASTA, Genbank,...), access to online services (NCBI, Expasy,...), interfaces to commonand not-so-common programs (Clustalw, DSSP, MSMS...), a standard sequence class, various clusteringmodules, a KD tree data structure etc.
Table of contents
- Introduction
- Quick Start - What can you do with Biopython?
- Sequence objects
- Sequence annotation objects
- Sequence Input/Output
- Multiple Sequence Alignment objects
- BLAST
- BLAST and other sequence search tools
- Accessing NCBI's Entrez databases
- Swiss-Prot and ExPASy
- Going 3D: The PDB module
- Bio.PopGen: Population genetics
- Phylogenetics with Bio.Phylo
- Sequence motif analysis using Bio.motifs
- Cluster analysis
- Supervised learning methods
- Graphics including GenomeDiagram
- KEGG
- Bio.phenotype: analyse phenotypic data
- Cookbook - Cool things to do with it
- The Biopython testing framework
- Advanced
- Where to go from here - contributing to Biopython
| Pages : | 360 |
| Size : | 3.0 MB |
| Downloads: | 124 |
| Created: | 2022-02-01 |
| License: | Open Publication License |
| Author(s): | by Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich, Bartek Wilczy?ski |
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