Sequences.
A core concept in Biopython is the biological sequence, and this is represented by the Seq class. A Biopython Seq object is similar to a Python string in many respects: it supports the Python slice notation, can be concatenated with other sequences and is immutable.
Sequence annotation.
The SeqRecord class describes sequences along with information such as name description and features in the form of SeqFeature objects. Each SeqFeature object specifies the type of the feature and its location.
Feature types can be gene CDS coding sequence repeat_region mobile_element or others, and the position of features in the sequence can be exact or approximate.
Input and output.
Biopython can read and write to a number of common sequence formats, including FASTA, FASTQ, GenBank, Clustal, PHYLIP and NEXUS
Phylogeny.
The Bio.Phylo module provides tools for working with and visualising phylogenetic trees
Genome diagrams.
The GenomeDiagram module provides methods of visualizing sequences within Biopython.
Population genetics.
Bio.PopGen module adds support to Biopython for Genepop, a software package for statistical analysis of population genetics. This allows for analyses of Hardy–Weinberg equilibrium, linkage disequilibrium and other features of a population's allele frequencies
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- History:
Began in 1999 and it was first released in July 2000. It was developed during a similar time frame and with analogous goals to other projects that added bioinformatics capabilities to their respective programming languages, including BioPerl, BioRuby and BioJava.
- Design:
Follows the conventions used by the Python programming language to make it easier for users familiar with Python. For example, Seq and SeqRecord objects can be manipulated via slicing, in a manner similar to Python's strings and lists. #DataVisualization
Browsing Data Compendia:
This is a good strategy if you are not sure what types of variables exist or what data would be relevant for your project
- Select a data compendia
- Determine the subject area or data type that your topic or variable falls under
- Read the descriptions
Searching by Topic:
This guide provides several links to data sources by topic. These links are by no mean exhaustive, but can be a good place to start and can help you get a sense of who are some of the major collectors of data in your topic area.