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.
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.
Consists in a collection of manually drawn pathway maps. KEGG PATHWAY concerns mainly molecular interaction, reaction and relation networks for: (1) drug development; (2) human diseases; (3) organismal systems; (4) cellular processes; (5) environmental information processing; (6) genetic information processing; (7) and metabolism. The identification of each pathway map is made thanks to a combination of 2-4 letter prefix code and 5-digit number.
Provides models of dynamic regulation of all genes in Methanococcus maripaludis. MMP was created by generating a comprehensive list of coding and noncoding RNAs through comparative analysis of the complete transcriptome and a comprehensive PeptideAtlas for M. maripaludis. It offers a model of global H2 regulation of methanogenesis in a hydrogenotrophic methanogen.
A probabilistic functional gene network of 18,714 validated protein-encoding genes of Homo sapiens, constructed by a modified Bayesian integration of 21 types of 'omics' data from multiple organisms, with each data type weighted according to how well it links genes that are known to function together in H. sapiens. Each interaction in HumanNet has an associated log-likelihood score (LLS) that measures the probability of an interaction representing a true functional linkage between two genes.
Allows to visualize modified ribosomal nucleotides of human, Arabidopsis, S. cerevisiae, H. marismortui, E. coli and T. thermophilus. 3D Ribosomal Modification Maps Database permits nucleotide modification data for several major model organisms. It offers an interface to control the visibility of the modified nucleotides and the different molecular components of the ribosome. This database facilitates 3D visualization of tRNA nucleotides, for example modified nucleotides within ribosome-bound tRNAs.
Aims at providing a central platform for yeast genetic network analysis and visualization. DRYGIN holds more than 5.4 million measurements of genetic interacting pairs involving 4500 genes. It associates the genetic interactions with pathway information, protein complexes, other binary genetic and physical interactions, and Gene Ontology (GO) functional annotation. The tool will be central Saccharomyces cerevisiae resource assisting experimentalists in the generation of testable hypotheses.
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.
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.
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.
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.
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.
Provides a data resource for autophagy researches. ARN collects up to 1480 proteins with more than 4000 of autophagy components in humans. It also contains more than 400 transcription factors (TF) and 380 miRNA that can serve to adjust autophagy components and their protein regulators including signaling pathways from the SignaLink 2 resource. Disease and cancer type annotations are available for each protein in this database.
Contains several information and literature about Adipogenesis Regulation Network. ARN is a database of molecule-molecule regulatory interactions identified via the manual curation of PubMed abstracts. It includes more than 53500 records related to adipogenic differentiation and represents one of the more largest source of literature-curated adipogenesis regulatory interactions.
Assists searches of module networks by using prostate cancer expression data collected via the LeMoNe algorithm. ProNet allows users to search for a gene via four fields: gene description, Illumina gene code, common name gene (Hugo symbol) and module number. The application displays interactive results providing a detailed list of the module genes and regulators.
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.
Provides Mycobacterium tuberculosis (MTB) regulatory network data. MTB Network Portal was constructed on the basis of large-scale ChIP-seq and expression analyses. It offers detailed definitions of these two datasets, associated analysis workflows, integration with an independent gene regulatory network (GRN) model and description of an accessible web-based resource for further data access and exploration.
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.
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.
Provides easy access to a total of 3,103 known regulations in C. glutamicum ATCC 13032 and M. tuberculosis H37Rv and to 38,940 evolutionary conserved interactions for 18 non-model species of the CMNR group. This makes CMRegNet to date the most comprehensive database of regulatory interactions of CMNR bacteria. CMRegNet is accessible by a user-friendly online interface.
Provides data about miRNA-gene target interactions (MTIs) and miRNA-gene target regulatory networks (MGRNs). CormiRNet was constructed using a combined data-mining approach. It can serve to explore many possible biological scenarios. This database assists users to detect unknown functional similarities or synergies among miRNAs and among target genes. It provides hyperlinks to several external resources.
Enables users to construct, visualise and analyse Gene Regulatory Network (GRNs) in multi-cellular organisms. myGRN is a relational database that acts as a repository for interaction data. It also integrates data from multiple labs to generate unified networks and provides a simple interface that allows for complex and flexible querying of the data. This approach can be used for GRNs in any context.
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.
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.
Provides regulatory interactions in cyanobacteria. RegCyanoDB contains 20,280 interactions with confidence levels for 30 cyanobacterial strains. It provides the computationally predicted regulatory interactions in cyanobacteria, mapped from the most well-studied organism, E. coli. The database permits to give a better idea for using the interactions in experimental or computational applications.
Provides access to over-expression experiments in Arabidopsis T87 cultured cells. RnR is a database allowing users to submit a gene or metabolite to study regulatory relationship between gene and metabolites.
Gives access to various types of cancer information in KEGG. KEGG Cancer is an interface which includes KEGG PATHWAY, KEGG BRITE, KEGG DISEASE, KEGG DRUG, KEGG COMPOUND, and KEGG GLYCAN databases. The database also provides cancer pathway mapping tools.
Allows detection of clinically relevant miRNAs that are candidates for improved diagnostics, prognostics and therapeutics. Cancer miRNA Regulatory Network has been built by inferring miRNA mediated regulation for more than 2 200 gene co-expression signatures from about 50 cancer transcriptome profiling studies.
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).
Consists of two modules - a database of regulatory interactions based on literature and an expertly curated database of transcription factor binding sites. This literature based information in RegTransBase is a manually curated database of regulatory interactions in prokaryotes. RegTransBase captures the knowledge in published scientific literature using a controlled vocabulary.
Integrates several methods concerning microarray data pretreatment, microarray data statistical and clustering analysis, genome-wide iterative enrichment analysis and motif discovery. CRSD is an online repository that can be used to investigate complex regulatory behaviors involving gene expression signatures (GESs), microRNA regulatory signatures (MRSs) and transcription factors (TF) regulatory signatures (TRSs).
A web interface to the aMAZE relational database, which contains information on gene expression, catalysed chemical reactions, regulatory interactions, protein assembly, as well as metabolic and signal transduction pathways.
Compiles data about the pseudomonas. SYSTOMONAS registers information on eight different Pseudomonas species and strains, which genomes have been completely sequenced and functionally annotated. The database contains information for all levels of analysis as microarray and proteomics data, metabolite measurements, sequence data, gene-regulatory networks (GRNs) and corresponding enzyme data.
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