1.Basic Local Alignment Search Tool (BLAST) is a sequence comparison algorithm optimized for speed and used to search DNA and protein sequence databases for optimal local alignments to a query.
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2.CLC Assembly Cell is a high-performance computing solution for read mapping and de novo assembling of next generation sequencing data. With the command-line interface of CLC Assembly Cell, you can easily include these functionalities in scripts and other next generation sequencing workflows. It is easy to install on your desktop computer or a larger compute cluster. CLC Assembly Cell is accelerated through advanced algorithm implementations: they use the SIMD instruction set to parallelize and accelerate compute intensive parts of the algorithms, and make the software one of the fastest and most accurate packages for NGS data analysis on the market.
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3.Gero is a drug discovery company creating first in class small molecule therapeutics using proprietary, industry leading molecular modeling methods and systems biology technologies.
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4.Glide offers the full range of speed vs. accuracy options, from the HTVS (high-throughput virtual screening) mode for efficiently enriching million compound libraries, to the SP (standard precision) mode for reliably docking tens to hundreds of thousands of ligand with high accuracy, to the XP (extra precision) mode where further elimination of false positives is accomplished by more extensive sampling and advanced scoring, resulting in even higher enrichment.
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5.HMMER is used for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). HMMER is often used together with a profile database, such as Pfam or many of the databases that participate in Interpro. But HMMER can also work with query sequences, not just profiles, just like BLAST.
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6.MrBayes is a program for the Bayesian estimation of phylogeny. Bayesian inference of phylogeny is based upon a quantity called the posterior probability distribution of trees, which is the probability of a tree conditioned on the observations. The conditioning is accomplished using Bayes’s theorem. The posterior probability distribution of trees is impossible to calculate analytically; instead, MrBayes uses a simulation technique called Markov chain Monte Carlo (or MCMC) to approximate the posterior probabilities of trees.
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