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http://www.bacteriome.org

Database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase. Presently the resource offers access to two types of network: * A network of functional interactions derived through exploiting available functional genomic datasets within a Bayesian framework * Two networks of experimentally derived protein-protein interactions - a "core" network consisting of interactions deemed to be of "high quality"; and an "extended" network which extends the "core" network by including interactions for which experimental evidence is less strong.

Proper citation: Bacteriome.org (RRID:SCR_001934) Copy   

•   Source: SciCrunch Registry

http://www.transcriptionfactor.org/index.cgi?Home

Database of predicted transcription factors in completely sequenced genomes. The predicted transcription factors all contain assignments to sequence specific DNA-binding domain families. The predictions are based on domain assignments from the SUPERFAMILY and Pfam hidden Markov model libraries. Benchmarks of the transcription factor predictions show they are accurate and have wide coverage on a genomic scale. The DBD consists of predicted transcription factor repertoires for 930 completely sequenced genomes.

Proper citation: DBD: Transcription factor prediction database (RRID:SCR_002300) Copy   

•   Source: SciCrunch Registry

http://drtf.cbi.pku.edu.cn/

Database collection of known and predicted transcription factors of Oryza sativa L. ssp. indica and Oryza sativa L. ssp. japonica. DRTF currently contains 2,025 putative transcription factors (TF) gene models in indica and 2,384 in japonica, distributed in 63 families. THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026.

Proper citation: Database of Rice Transcription Factors (RRID:SCR_002413) Copy   

•   Source: SciCrunch Registry

http://mips.helmholtz-muenchen.de/genre/proj/corum

Database of manually annotated protein complexes from mammalian organisms. Annotation includes protein complex function, localization, subunit composition, literature references and more. All information is obtained from individual experiments published in scientific articles, but data from high-throughput experiments is excluded.
The majority of protein complexes in CORUM originates from man (65%), followed by mouse (14%) and rat (14%)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CORUM (RRID:SCR_002254) Copy   

•   Source: SciCrunch Registry

http://genecards.org

Database of human genes that provides concise genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. Information featured in GeneCards includes orthologies, disease relationships, mutations and SNPs, gene expression, gene function, pathways, protein-protein interactions, related drugs and compounds and direct links to cutting edge research reagents and tools such as antibodies, recombinant proteins, clones, expression assays and RNAi reagents.

Proper citation: GeneCards (RRID:SCR_002773) Copy   

•   Source: SciCrunch Registry

http://www.coryneregnet.de

Reference database and analysis platform for corynebacterial transcription factors and gene regulatory networks. It generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure.

Proper citation: CoryneRegNet (RRID:SCR_002255) Copy   

•   Source: SciCrunch Registry

http://mmonot.eu/COV2HTML/connexion.php

An interactive web interface addressed to biologists, allowing both coverage visualization and analysis of NGS alignments performed on prokaryotic organisms (bacteria and phages). Its strength is to make NGS analysis without software installation, login or long training period.

Proper citation: COV2HTML (RRID:SCR_002886) Copy   

•   Source: SciCrunch Registry

http://zfin.org

Model organism database that serves as central repository and web-based resource for zebrafish genetic, genomic, phenotypic and developmental data. Data represented are derived from three primary sources: curation of zebrafish publications, individual research laboratories and collaborations with bioinformatics organizations. Data formats include text, images and graphical representations.Serves as primary community database resource for laboratory use of zebrafish. Developed and supports integrated zebrafish genetic, genomic, developmental and physiological information and link this information extensively to corresponding data in other model organism and human databases.

Proper citation: Zebrafish Information Network (ZFIN) (RRID:SCR_002560) Copy   

•   Source: SciCrunch Registry

http://phylogenomics.blogspot.fr/

Blog by evolutionary biologist and UC Davis professor Jonathan Eisen. Topics of his posts include microbiology, phylogenomics, product reviews, and a variety of miscellaneous topics.

Proper citation: Tree of Life (RRID:SCR_002436) Copy   

•   Source: SciCrunch Registry

http://t3db.org/

Database that combines detailed toxin data with comprehensive toxin target information. The database currently houses 3,053 toxins described by 32,276 synonyms, including pollutants, pesticides, drugs, and food toxins, which are linked to 1,670 corresponding toxin target records. Altogether there are 37,084 toxin, toxin target associations. (March 2014) Each toxin record (ToxCard) contains over 50 data fields and holds information such as chemical properties and descriptors, toxicity values, molecular and cellular interactions, and medical information. This information has been extracted from over 5,454 sources sources, which include other databases, government documents, books, and scientific literature. The focus of the T3DB is on providing mechanisms of toxicity and target proteins for each toxin. This dual nature of the T3DB, in which toxin and toxin target records are interactively linked in both directions, makes it unique from existing databases. It is also fully searchable and supports extensive text, sequence, chemical structure, and relational query searches

Proper citation: T3DB (RRID:SCR_002672) Copy   

•   Source: SciCrunch Registry

http://ecocyc.org/

Database for the bacterium Escherichia coli K-12 MG1655, the EcoCyc project performs literature-based curation of the entire genome, and of transcriptional regulation, transporters, and metabolic pathways. The long-term goal of the project is to describe the molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists, and for biologists who work with related microorganisms.

Proper citation: EcoCyc (RRID:SCR_002433) Copy   

•   Source: SciCrunch Registry

http://mint.bio.uniroma2.it/domino/

Open-access database comprising more than 3900 annotated experiments describing interactions mediated by protein-interaction domains. The curation effort aims at covering the interactions mediated by the following domains (SH3, SH2, 14-3-3, PDZ, PTB, WW, EVH, VHS, FHA, EH, FF, BRCT, Bromo, Chromo, GYF). The interactions deposited in DOMINO are annotated according to the PSI MI standard and can be easily analyzed in the context of the global protein interaction network as downloaded from major interaction databases like MINT, INTACT, DIP, MIPS/MPACT. It can be searched with a versatile search tool and the interaction networks can be visualized with a convenient graphic display applet that explicitly identifies the domains/sites involved in the interactions.

Proper citation: DOMINO: Domain peptide interactions (RRID:SCR_002392) Copy   

•   Source: SciCrunch Registry

http://www.drugbank.ca/

Bioinformatics and cheminformatics database that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information.

Proper citation: DrugBank (RRID:SCR_002700) Copy   

•   Source: SciCrunch Registry

https://epd.expasy.org/epd/

EPDnew databases are the result of merging Eukaryotic Promoter Database, EPD, promoters within house analysis of promoter specific high throughput data for selected organisms only. EPDnew is a set of species specific databases of experimentally validated promoters.

Proper citation: EPDnew (RRID:SCR_002485) Copy   

•   Source: SciCrunch Registry

http://hint.yulab.org/

A database of high-quality protein-protein interactions in different organisms.

Proper citation: HINT (RRID:SCR_002762) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gene

Database for genomes that have been completely sequenced, have active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. Includes nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases. All entries follow NCBI's format for data collections. Content of Entrez Gene represents result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. Content is updated as new information becomes available.

Proper citation: Entrez Gene (RRID:SCR_002473) Copy   

•   Source: SciCrunch Registry

http://dbtss.hgc.jp/

Database of transcriptional start sites (TSSs) representing exact positions in the genome based on a unique experimentally validated TSS sequencing method, TSS Seq. A major part of human adult and embryonic tissues are covered. DBTSS contains 491 million TSS tag sequences collected from a total of 20 tissues and 7 cell cultures. Also integrated is generated RNA-seq data of subcellular- fractionated RNAs and ChIP Seq data of histone modifications, RNA polymerase II and several transcriptional regulatory factors in cultured cell lines. Also included is external epigenomic data, such as chromatin map of the ENCODE project. They associated those TSS information with public and original SNV data, in order to identify single nucleotide variations (SNVs) in the regulatory regions.

Proper citation: DBTSS: Database of Transcriptional Start Sites (RRID:SCR_002354) Copy   

•   Source: SciCrunch Registry

http://machibase.gi.k.u-tokyo.ac.jp/

Database for Drosophila melanogaster transcription profiling that allows users to search the Drosophilia genome, see sequence overviews, and look at various transcripts. The data were generated in conjunction with the recently developed high-throughput genome sequencer Illumina / Solexa using a newly developed 5'-end mRNA collection method. Approximately 25 million 25-27 nucleotide (nt) 5'-end mRNA tags from the embryos, larvae, young males, young females, old males, old females, and S2 (culture cell line) of D. melanogaster were collected. By arranging this vast amount of expression tag with other annotated data, they have built a one-stop service for Drosophila melanogaster transcription profiling.

Proper citation: MachiBase (RRID:SCR_003078) Copy   

•   Source: SciCrunch Registry

http://genome.ufl.edu/mapper/

A platform composed of three modules: the Database, the Search Engine, and rSNPs, for the computational identification of transcription factor binding sites (TFBSs) in multiple genomes, that combines TRANSFAC and JASPAR data with the search power of profile hidden Markov models (HMMs). The Database contains putative TFBSs found in the upstream sequences of genes from the human, mouse and D.melanogaster genomes. For each gene, they scanned the region from 10,000 base pairs upstream of the transcript start to 50 base pairs downstream of the coding sequence start against all their models. Therefore, the database contains putative binding sites in the gene promoter and in the initial introns and non-coding exons. Information displayed for each putative binding site includes the transcription factor name, its position (absolute on the chromosome, or relative to the gene), the score of the prediction, and the region of the gene the site belongs to. If the selected gene has homologs in any of the other two organisms, the program optionally displays the putative TFBSs in the homologs. The Search Engine allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, D.melanogaster, C.elegans or S.cerevisiae genomes. In addition, it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. rSNPs MAPPER is designed to identify Single Nucleotide Polymorphisms (SNPs) that may have an effect on the presence of one or more TFBSs.

Proper citation: MAPPER - Multi-genome Analysis of Positions and Patterns of Elements of Regulation (RRID:SCR_003077) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org/codehop.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.Service to design PCR primers from protein multiple sequence alignments. NOTICE: This version of CODEHOP is no longer maintained.

Proper citation: CODEHOP (RRID:SCR_002898) Copy   

•   Source: SciCrunch Registry