We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
Improved mapper for bisulfite sequencing reads on DNA methylation.
An approach for the analysis of two-base encoding bisulfite sequencing data.
A high-efficiency and easy-to-use analysis pipeline for MeRIP-Seq peak-finding at high resolution, which compares distributions of reads between immunoprecipitation sample and control sample.
A peak-caller for CLIP- and RIP-Seq data. It takes input in BED or BAM format and identifies regions of significant read enrichment. Additional covariates may optionally be provided to further inform the peak-calling process., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
A hidden Markov model (HMM)-based software to predict clusters RNA motif sites.
A public database that provides the complete transcription factor (TF) repertoires of 6 genome sequenced tree species: papaya (Carica papaya), jatoropha (Jatropha curcas), cassava (Manihot esculenta), poplar (Populus trichocarpa), castor bean (Ricinus communis) and grape vine (Vitis vinifera). from annotated genes on each genome.
A Knowledge Database of Soybean Transcription Factors. PSI-BLAST is available to find hits from the database.
Public database arising from efforts to identify and catalogue all plant genes involved in transcriptional control.Integrative plant transcription factor database that provides web interface to access large sets of transcription factors of several plant species, currently encompassing Arabidopsis thaliana (thale cress), Populus trichocarpa (poplar), Oryza sativa (rice), Chlamydomonas reinhardtii and Ostreococcus tauri. Provides access point to its daughter databases of species-centered representation of transcription factors (OstreoTFDB, ChlamyTFDB, ArabTFDB, PoplarTFDB and RiceTFDB). Information including protein sequences, coding regions, genomic sequences, expressed sequence tags, domain architecture and scientific literature is provided for each family.
A web-based analysis tool that is designed to identify and categorize plant TF/TR/CR genes from genome-scale protein and nucleic acid sequences by systematically analyzing InterProScan domain patterns in protein sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
A phylogeny-based comprehensive database of plant transcription associated proteins.
A public database that provides predicted transcription factor (TF) encoding genes annotated in genome sequences of three major legume species: soybean (Glycine max), Lotus japonicus and Medicago truncatula.
A R/Bioconductor package for a flexible and fast recognition of nucleosome positioning from next generation sequencing and tiling arrays experiments. The software is integrated with standard high-throughput genomics R packages and allows for in situ visualization as well as to export results to common genome browser formats.
Software for inferring nucleosome positions with their histone mark annotation from ChIP data. It is a versatile tool that can be used to predict positioned nucleosomes from one or multiple ChIP-seq bam files and it can be also used in conjunction with a control experiment.
An R package mapping nucleosome-linker boundaries from both MNase-Chip and MNase-Seq data using a non-homogeneous hidden-state model based on first order differences of experimental data along genomic coordinates.
An online server that can be used to identify binding sites of known transcription factors, which further incorporates nucleosome occupancy around sites on promoter regions, thereby improving the accuracy of predition.
A multithreaded Java application for finding positioned nucleosomes from sequencing data.
A python software package that can identify nucleosome positions given histone-modification ChIP-seq or nucleosome sequencing at the nucleosome level.
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.