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A command line software tool for accurate placing of the nucleosomes using a Modified Gaussian Mixture Model. It was designed to resolve overlapping nucleosomes and extract extra information (fuzziness, probability, etc.) of nucleosome placement. To achieve this goal the tool clusters the input tags according to Nucleosome Model (see the paper for detailed description) using EM learning process. The tool is written in C++. There are no special requirements except for g++ compiler and *nix environment to compile and use the tool. It was checked to compile using g++ compiler under Ubuntu 11.04 and Mac OS X 10.6
Software for Transcription Factor Flexible Models (TFFMs) that represent Transcription Factor Binding Sites (TFBSs) and are based on hidden Markov models (HMM). They are flexible and are able to model both position interdependence within TFBSs and variable length motifs within a single dedicated framework.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A Software program for Predicting Transcription Factor Binding Sites.
Software tool that predicts motifs in full-size peak sets. It performs all steps from motif discovery to visualization of the predicted sites in genome browsers., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Web server that, starting from a collection of genomic regions derived from a ChIP-Seq experiment, scans them using motif descriptors like JASPAR or TRANSFAC position-specific frequency matrices, or descriptors uploaded by users, and it evaluates both motif enrichment and positional bias within the regions according to different measures and criteria.
A web-based system for the detection of over-represented conserved transcription factor binding sites and binding site combinations in sets of genes or sequences.
An integrated web tool for transcription factor binding site search and visualization. Both the Python Scripts for Offline Scanning and the Python implementation of the LASAGNA algorithm are available., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
A webserver built on the Galaxy framework that enables the mining of sequence data for transcription factor binding sites. This tool suite was designed to aid in analysis of next-generation sequencing (NGS) data that uses a support vector machine (SVM) with kmer sequence features to identify predictive combinations of short transcription factor binding sites which determine the tissue specificity of the original NGS assay. While you may use datasets already available from Galaxy, you can upload your data using the ''Get Data'' Tool. The tool can upload data from a variety of locations.
Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.
A software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser.
Software for motif discovery using dinucleotide position weight matrices (PWMs).
Data analysis service providing a motif discovery platform developed to help biologists to find novel as well as known motifs in their peak datasets from transcription factor (TF) binding experiments such as ChIP-seq and ChIP-chip.
A software tool for systematic discovery of transcription factors and their cofactors from ChIP-seq data.
Software for harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures.
A software program which finds sequence elements conserved in a set of DNA sequences.
R-package for identifying differential ChIP-seq based on an ensemble of mixture models.
Finding differential chromatin modification sites from ChIP-seq data.
Detects differential binding of transcription factors with ChIP-seq.
Provides a solution for the identification of Differential Histone Modification Sites (DHMSs) by comparing two ChIP-seq libraries (L1 and L2).
R package for comparative analysis of RNA Polymerase II ChIP-Seq profiles by non-linear normalization.