Open Source Python Bio-Informatics Software

CBFLIB is a library of ANSI-C functions providing a simple mechanism for accessing Crystallographic Binary Files (CBF files) and Image-supporting CIF (imgCIF) files. The CBFLIB API is loosely based on the CIFPARSE API for mmCIF files.

The Free DELTA Project is a free, open-source, software alternative for a generic system to the processing of taxonomic descriptions based on the DELTA (DEscription Language for TAxonomy) format.

The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.

This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...

StochPy - Stochastistic modeling in Python - is an easy-to-use package, which provides several stochastic simulation algorithms and unique analysis techniques, which can be used for stochastic simulations of biochemical systems.

TinkerCell is a software for synthetic biology. The visual interface allows users to design networks using various biological "parts". Models can include modules and multiple cells. Users can program new functions using C or Python. www.tinkercell.

Stochastic simulator for signaling pathways occuring in biological cells. Handles reaction-diffusion processes in 3D tetrahedral meshes. Please check our new repository: https://github.com/CNS-OIST/STEPS

""" E-Cell's source code repository has moved to GitHub! https://github.com/ecell The development of E-Cell now continues on GitHub. The Subversion repository was abandoned. """ E-Cell System is an object-oriented software suite for modeling, simulation, and analysis of large scale complex systems such as biological cells. It allows many components driven by multiple algorithms with different timescales to coexist in a model.

This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3 mining sites and bringing to the base. At the time the agent is born, it doesn't know how to walk nor it knows that it feels pleasure by mining. He has tact only (blind agent). The video shows learning, planning, executing and plan optimization.

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.

A univariate and multivariate analysis UI. This project is no longer under development. Please use as you wish.

A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining.

A set of very optimized tools for indexing/querying huge genomes/files. Provided so far: a very fast exact mapper, and an unconstrained split-mapper

The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.

This is the UNOFFICIAL mirror to PyMod. Since the release of PyMod2.0, this repository will no longer be maintained.

mitoMaker is a pipeline script developed to simplify the assembly and automatic annotation of mitochondrial genomes, based on raw NGS reads and an optional target reference. mitoMaker calls well known assemblers and algorithms, such as SOAPdenovo, MIRA and blast+ and parses their results providing easily readable outputs, such as FASTA, GENBANK, SEQUIN, PNG and others. General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).

The PyCogent project is moving to GitHub. When completed, you will find us at http://github.com/pycogent/pycogent/. You can find the PyCogent website at http://www.pycogent.org.

Amplicon is a Python script for designing PCR primer sets. Amplicon is written in Python 2.3 and Tkinter 8.4. The current script was created for Windows and an executable is available. Future versions of the script should be able to run on Linux and Mac

CoNIFER uses exome sequencing data to find copy number variants (CNVs) and genotype the copy-number of duplicated genes.

This is a library for creating and manipulating graphs with focus on speedy operations for large, sparse graphs.

vipR is a program to screen for sequence variants (SNPs, deletions) in sequence data generated by high-throughput-sequencing platforms. Information on this and other projects can be found on: http://www.altmann.eu

The Protein Geometry Database hosts the development code for a flexible database for searching protein geometry, as well as a library for accessing this data for protein modeling & refinement programs.

BARNACLE is a Python library for RNA 3D structure prediction. It can be used for probabilistic sampling of RNA structures that are compatible with a given nucleotide sequence and that are RNA like on a local length scale.

"Blue Planet" is a research project simulating the behaviour and darwinian evolution of unicellular lifeforms, each controlled by its own genetic program. Moreover, "Blue Planet Inhabitants" are suited for swarm intelligence and swarm research.

RADAR stands for Rapid Automatic Detection and Alignment of Repeats in protein sequences. RADAR identifies gapped approximate repeats and complex repeat architectures involving many different types of repeats. Radar has moved to github (https://github.com/AndreasHeger/radar)