Open Source Python Bio-Informatics Software for Mac

Microarray Gene Expression Database Group and OMG Gene Expression Standard (MAGE)

ECOLOG is a specimen-based, cross-platform relational database management system, aimed at the storage, retrieval and preliminary analysis of data on sites, species, and specimens gathered in ecological field surveys and biodiversity inventories. The main goal of ECOLOG is to make the data gathered in ecological field surveys readily accessible, providing lists of species collected in the study area and informations on habitat preferences, abundance or rarity of a given species, biometrics, morphology, dominance, and spatial location of each specimen collected in the field.

BioMa is a specimen based Biodiversity database Manager. It is designed to store, organize, and manipulate biodiversity-related scientific data, either for the purposes of museums, scientific collections, or research projects.

A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.

A Python library bringing together utilities I've written over the years for work in bioinformatics and biostatistics, which should be generally applicable outside these fields as well. Focuses on string processing, DBI, and math.

A database and a web front end for physiologic data on animal feeding, developed with PostgreSQL and Django at NESCent (http://www.nescent.org) for Mammalian Feeding Working Group (http://www.feedexp.org). Current development of the codebase is on Github at http://github.com/NESCent/feedingdb.

The purpose of this project is to make available a variety of tools written in Python.

A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining