BMT is combination of seven tools including FastqTrimmer, Gene Prediction, DNA Analysis, Translation, Protein analysis and Pairwise and Multiple alignment.
BioCRF is an implementation of Grammatical-Restrained Hidden Conditional Random Fields (GRHCRFs) , an extension of linear HCRF to include prior knowledge about the problem at hand by means of a regular grammar. This results very useful in several Bioinformatics problems where only solution that agree with a regular grammar rules are biologically meaningful.
BioHEL is an evolutionary learning system designed to handle with large-scale bioinformatic datasets.
BioHEL RPE is a standalone program which takes a set of rules generated with BioHEL and applies a series of memetic operators over the individual rules and the whole rule set to increase their generality and reduce their complexity.
M.A. Franco, N. Krasnogor, J. Bacardit Post-processing operators for decision lists
in Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference – GECCO ’12, p.847, Philadelphia, Pennsylvania, USA, 2012
The Taiji software is an integrative multi-omics data analysis framework. It can be used as a standalone pipeline to analyze ATAC-seq, RNA-seq, single cell ATAC-seq or Drop-seq data. However, the uniqueness and the power of Taiji really lie in its ability to integrate diverse datasets and use these information in a clever way to construct regulatory network and identify candidate driver genes.
birgHPC (Bioinformatic Research Group High Performance Computing) is a free Linux Live CD distribution based on PelicanHPC and Debian Live.birgHPC features automated cluster configuration on PCs in the same network specifically for bioinformatics and molecular dynamics.
The DART (DNA, Amino and RNA Tests.)library includes a number of bioinformatics programs, including: stemloc for RNA alignment; xrate for phylo-grammars; phylocomposer and other statistical alignment programs in the Handel package; and more.The programs use statistical algorithms (MCMC, EM) to impute multiple alignments, annotations and other unseen evolutionary parameters from sequence data. All are based on stochastic grammars or state-machine models of sequence mutation and natural selection.