DNA motif finding software tools | Genome annotation
De-novo motif search is a frequently applied bioinformatics procedure to identify and prioritize recurrent elements in sequences sets for biological investigation, such as the ones derived from high-throughput differential expression experiments. Several algorithms have been developed to perform motif search, employing widely different approaches and often giving divergent results.
Gives access to many free software tools for sequence analysis. EMBOSS aims to serve the molecular biology community. It permits the creation and the release of software in an open source spirit. This tool is useful for sequence analysis into a seamless whole. It is free of charge and is available in open source.
Discovers novel, ungapped motifs (recurring, fixed-length patterns) in your nucleotide or protein sequences (sample output from sequences). MEME splits variable-length patterns into two or more separate motifs. MEME is part of the MEME Suite online platform.
A modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations.
Allows users to search whole prokaryotic genomes for intrinsic terminators. TransTermHP permits prediction of Rho-independent transcription termination in bacterial genomes. This method assists in the detection of signals in genomic DNA. It assigns each candidate terminator a score related to the likelihood that it arose by chance. Moreover, it is designed to detect the common, classic intrinsic terminator motif: a hairpin stem followed by a poly-U tail.
Examines the upstream region of genes in the same gene expression pattern group and looks for regulatory sequence motifs. BioProspector uses zero to third-order Markov background models whose parameters are either given by the user or estimated from a specified sequence file. The significance of each motif found is judged based on a motif score distribution estimated by a Monte Carlo method. In addition, BioProspector modifies the motif model used in the earlier Gibbs samplers to allow for the modeling of gapped motifs and motifs with palindromic patterns.
Investigates biological patterns. PatScan is an application based on the use of an expressive pattern language to detect predetermined DNA and protein sequence patterns. Users have the possibility to look for repeats, hairpins, stem loops or pseudoknots. The application can be run under a command-line interface for researchers with advanced skills or as a simplified web interface exploiting a drag & drop system.
A motif sampling algorithm that runs on arbitrary collections of multiple local sequence alignments of orthologous sequences. The algorithm searches over all ways in which an arbitrary number of binding sites for an arbitrary number of transcription factors (TFs) can be assigned to the multiple sequence alignments. These binding site configurations are scored by a Bayesian probabilistic model that treats aligned sequences by a model for the evolution of binding sites and "background" intergenic DNA. This model takes the phylogenetic relationship between the species in the alignment explicitly into account.