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SCoPNet / Seed Co-Prediction Network
Provides the result of coprediction network using BioHEL with the Arabidopsis seed gene expression training set. SCoPNet is a computational methodology provides more of 13,500 nodes and 146,500 edges. It represents a useful alternative approach for the extraction of biological knowledge from existing data while other approaches are not capable of inferring. This resource could serve in diverse areas of plant biology in the elucidation of functional networks and increases the return on the collective investment made by the research community in the generation of large-scale data sets.
Allows discovery of conserved regulatory relations in eight eukaryotic model organisms. ConReg is an online system, for analyzing and visualizing regulatory networks and their conservation, that consists of two features: The Conservation Browser, where the entire predicted conserved network is shown and the Motif Finder which allows user to search for conservations in a defined subset of genes. It also provides direct links to annotations including literature references to potentially conserved regulatory relations. ConReg is also available as a Cytoscape plug-in.
PAHKB / Pulmonary Arterial Hypertension KnowledgeBase
A comprehensive database committed to establishing a comprehensive resource for pulmonary arterial hypertension. PAHKB extracts genetic data from all available sources, including those from association studies, genetic mutation, gene expression, animal model, supporting literature, various genomic annotations, gene networks, cellular and regulatory pathways, as well as microRNAs. Moreover, PAHKB provides online tools for data browsing and searching, data integration, pathway graphical presentation, and gene ranking.
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Offers a way to search and discover the relationships among genes, proteins, compounds and small RNAs in plant signal transduction, metabolism and gene regulatory networks. HRGRN models the interactions between nodes by defining comprehensive types of edges. It provides connection by edges between the genes with similar expression patterns, which will provide in-depth insight into gene–gene relationships. The database permits to discover novel interactions between genes and/or pathways and the built-in analysis tool available on the site allows to build subnetworks for specified nodes based on known interactions.
Regulatory circuits
A comprehensive resource of 394 cell type- and tissue-specific gene regulatory networks for human, each specifying the genome-wide connectivity among transcription factors, enhancers, promoters and genes. Integration with 37 genome-wide association studies (GWASs) showed that disease-associated genetic variants-including variants that do not reach genome-wide significance-often perturb regulatory modules that are highly specific to disease-relevant cell types or tissues. Our resource opens the door to systematic analysis of regulatory programs across hundreds of human cell types and tissues.
TRED / Transcriptional Regulatory Element Database
A mammalian Transcriptional Regulatory Element Database with associated data analysis functions. TRED collects cis- and trans-regulatory elements and is dedicated to easy data access and analysis for both single-gene-based and genome scale studies. Distinguishing features of TRED include: (i) relatively complete genome-wide promoter annotation for human, mouse and rat; (ii) availability of gene transcriptional regulation information including transcription factor binding sites and experimental evidence; (iii) data accuracy is ensured by hand curation; (iv) efficient user interface for easy and flexible data retrieval; and (v) implementation of on-the-fly sequence analysis tools. TRED can provide good training datasets for further genome-wide cis-regulatory element prediction and annotation, assist detailed functional studies and facilitate the decipher of gene regulatory networks.
Facilitates network analysis and gene annotation by (i) presenting co-expression networks with gene expression views in multiple dimensions (tissue-preferential and stress-differential expression profiling), (ii) establishing a comparative analysis between diploid and allotetraploid cotton, such as subnetwork features and histone modifications of genes, and (iii) using functional enrichment tools, such as functional co-expression modules and gene set analyses. The ccNET database aims to provide an online database server for comparative gene functional analyses at a multidimensional network and epigenomic level across diploid and polyploid Gossypium species.
ESCAPE / Embryonic Stem Cell Atlas from Pluripotency Evidence
A mouse and human embryonic stem cells (m/hESC)-centered database integrating data from many recent diverse high-throughput studies including chromatin immunoprecipitation followed by deep sequencing, genome-wide inhibitory RNA screens, gene expression microarrays or RNA-seq after knockdown (KD) or overexpression of critical factors, immunoprecipitation followed by mass spectrometry proteomics and phosphoproteomics. The database provides web-based interactive search and visualization tools that can be used to build subnetworks and to identify known and novel regulatory interactions across various regulatory layers. The web-interface also includes tools to predict the effects of combinatorial KDs by additive effects controlled by sliders, or through simulation software implemented in MATLAB.
Network portal / A Database for Storage Analysis and Visualization of Biological Networks
Provides an access to the inference, storage, exploration and visualization of gene-regulatory networks (GRNs). Network portal is linked to a network-inference pipeline which can generate networks for any organism (prokaryotic or eukaryotic) by using gene expression data from public databases or custom user files. Users can run analysis thanks to several tools for visualization, basic and advanced search interfaces and easy-to-use filters to explore and analyze regulation and gene function.
EGRIN / Environment and Gene Regulatory Influence Network
Provides a gene-gene association network. EGRIN models the condition specific global transcriptional state of the cell as a function of combinations of transient transcription factor (TF)-based control mechanisms acting at intergenic and intragenic promoters across the entire genome. It explains how microbes tailor transcriptional responses to varied environments by linking the genome-wide distribution of gene regulatory elements (GREs) to their organization and conditional activities.
TSmiR / Tissue Specific miRNA database
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A web-searchable database which provides information on interaction maps of transcription factor (TF) and tissue-specific (TS) miRNAs from experimentally validated and predicted data. TSmiR covers 116 TS miRNAs, 101 transcription factors and 2,347 TF-miRNAs regulatory relations in 12 tissues. Furthermore, experimentally validated expression data of TF and TS miRNA was also collected. The user can use the “search-by keyword” or “search-by category” function to retrieve the TF-TS miRNA regulatory relations. In addition to browsing TSmiR, there is a “browse” button at the top of the web page which allows users to explore TSmiR by clicking 12 different tissues.
TRRUST / Transcriptional Regulatory Relationships Unravelled by Sentence-based Text-mining
A manually curated database of human transcriptional regulatory network. Current version of TRRUST contains 8,015 transcriptional regulatory relationships between 748 human transcription factors (TFs) and 1,975 non-TF genes, derived from 6,175 pubmed articles, which describe small-scale experimental studies of transcriptional regulations. A sentence based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. TRRUST database also provide information of mode of regulation (activation or repression). Currently 4,861 (60.6%) regulatory relationships are known for mode of regulation.
miRDR / microRNA Dynamic Regulation Database
Provides data about dynamic miRNA-gene interactions, particularly focusing on the conditional interactions that are associated with tumor progression in multiple human cancers. miRDR concerns cancers from seven tissues including lung, kidney, stomach, breast, liver, uterine, and pancreas, and miRNA-mRNA interactions associated with each specific cancer. This database was constructed thanks to the integrative computational method named miRDR.
Gathers network data (metabolic, regulatory, protein-protein interaction) for 10 representative pathogenic Salmonella strains. SalmoNet is an online database regrouping information on interactions from multiple layers of biological organization. This repository allows users to study pathogen Salmonella with details in a standardized and documented format. It can be applied by medical microbiologists and epidemiologists to understand the strain specific differences of Salmonella.
A knowledge-based database of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data.
SoyFN / Soybean (Glycine max) Functional Network
A comprehensive web tool about soybean functional gene network (SoyFGN) and microRNA functional network (SoymiRFN). SoyFN contains all 37827 genes of the release of UniprotKB version 111 and all 555 mature miRNAs of the latest release of miRBase (Release 19: August 2012). You can compute any pair of soybean genes or miRNAs and get genes' 3'-UTRs. By using Cytoscape Web, the user can easily view his/her interesting genes or miRNAs in a network. Also, KEGG pathway, motif and genome browser are incorporated to analysis other types of function of miRNA and target genes of Soybean.
GSKB / Gene Set Knowledgebase
A comprehensive knowledgebase for pathway analysis in mouse. Interpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. GSKB is a functional genomics knowledgebase in mouse, which includes 33261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, 8747 lists of differentially expressed genes from 2526 published gene expression studies were manually collected and curated to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute the comprehensive Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA).
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