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http://www.orthomcl.org/cgi-bin/OrthoMclWeb.cgi

OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. OrthoMCL starts with reciprocal best hits within each genome as putative in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as putative ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.

Proper citation: OrthoMCL DB: Ortholog Groups of Protein Sequences (RRID:SCR_007839) Copy   

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http://metacyc.org/

MetaCyc is a database of nonredundant, experimentally elucidated metabolic pathways. MetaCyc contains more than 1,200 pathways from more than 1,600 different organisms, and is curated from the scientific experimental literature. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated compounds, enzymes, and genes.

Proper citation: MetaCyc (RRID:SCR_007778) Copy   

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http://merops.sanger.ac.uk/

An information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.

Proper citation: MEROPS (RRID:SCR_007777) Copy   

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http://locate.imb.uq.edu.au/

LOCATE is a curated database that houses data describing the membrane organization and subcellular localization of proteins from the RIKEN FANTOM4 mouse and human protein sequence set. The membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing peer-reviewed publications.

Proper citation: LOCATE: subcellular localization database (RRID:SCR_007763) Copy   

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http://snp500cancer.nci.nih.gov

It provides a central resource for sequence verification of SNPs. The goal of the SNP500Cancer project is to resequence 102 reference samples to find known or newly discovered single nucleotide polymorphisms (SNPs) which are of immediate importance to molecular epidemiology studies in cancer. The site allows users to search for SNPs using SNP identifier, gene symbol, gene alias, chromosome location, or gene ontology pathway.

Proper citation: SNP500Cancer (RRID:SCR_007943) Copy   

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http://snap.genomics.org.cn

A sequence analysis tool providing a simple but detailed analysis of human genes and their variations. For each gene, a gene-gene relationship network can be generated based on protein-protein interaction data, metabolic pathway connections and extended through phylogenetic relations. Snap provides tools for designing sequence primers and evaluating RNA splicing effects of single SNPs - known from the databases or defined by you. Primers can be designed for the amplification or sequencing of cDNA, genomic DNA, introns only or exons only., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SNAP (RRID:SCR_007936) Copy   

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http://natural.salk.edu/CREB/

CREB target gene database that uses a multi-layered approach to predict, validate and characterize CREB target genes. For each gene, the database tries to provide the following information: 1. CREB binding sites on the promoters 2. Promoter occupancy by CREB 3. Gene activation by cAMP in tissues CREB seems to occupy a large number of promoters in the genome (up to ~5000 in human), and the profiles for CREB promoter occupancy are very similar in different human tissues. However, only a small proportion of CREB occupied genes are induced by cAMP in any cell type, possibly reflecting the requirement of additional regulatory partners that assist in recruitment of the transcriptional apparatus. To use the database, choose the species, select the table you want to search, leave field (''All'') and type in the gene you want to search. A table listing the search results will be returned, followed by the description of the table. If no search result is returned, try the official gene symbol or gene ID (locuslink number) from NCBI Entrez Gene to search. Sponsors: This work was supported by National Institutes of Health Grants GM RO1-037828 (to M.M.) and DK068655 (to R.A.Y.).

Proper citation: CRE Binding-protein Target Gene Database (RRID:SCR_008027) Copy   

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http://www.mgc.ac.cn/VFs/

An integrated and comprehensive database of virulence factors for bacterial pathogens (also including Chlamydia and Mycoplasma). VFDB is a platform for further study of comparative pathogenomics. Major features include tabular comparison of pathogenomic composition in terms of virulence, multiple alignments and statistic analysis of homologous virulence genes, and graphical comparison of pathogenomic organization of VFs. Category: Genomics Databases (non-vertebrate) Subcategory: Prokaryotic genome databases

Proper citation: VFDB - Virulence Factors of Bacterial Pathogens (RRID:SCR_007969) Copy   

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http://tdrtargets.org/

This database functions both as a website where researchers can look for information on their targets of interest; and as a tool for prioritization of targets in whole genomes. Using the database as a tool, researchers can quickly prioritize a genome of interest by performing any number of individual queries on a species of interest, then assigning numerical weights to each query (in the history page) to finally obtain a ranked list of genes by combining the weighted queries. This site is part of a WHO/TDR project seeking to exploit the availability of diverse datasets to facilitate the identification and prioritization of drug targets in pathogens causing neglected diseases.

Proper citation: TDR Targets Database (RRID:SCR_007963) Copy   

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http://ppdb.tc.cornell.edu/

A Plant Proteome DataBase for Arabidopsis thaliana and maize (Zea mays). The PPDB stores experimental data from in-house proteome and mass spectrometry analysis, curated information about protein function, protein properties and subcellular localization. Importantly, proteins are particularly curated for possible (intra) plastid location and their plastid function. Protein accessions identified in published Arabidopsis (and other Brassicacea) proteomics papers are cross-referenced to rapidly determine previous experimental identification by mass spectrometry. All protein-encoding gene models in the Arabidopsis nuclear and organellar genomes, as assembled by TAIR, as well as all maize EST assemblies (ZmGI) as assembled by DFCI Maize Gene Index project. These are all uploaded in PPDB and are linked to each other via a BLAST alignment. Thus every predicted protein in both species can be searched for experimental and other information (even if not experimentally identified).

Proper citation: PPDB: Plant Proteomics Database (RRID:SCR_007872) Copy   

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http://www.poxvirus.org

A database of information on pox viruses. Goals of this project are to acquire and annotate data on poxviruses, and to develop and utilize new tools to facilitate the study of this group of organisms. This basic research is being undertaken with an eye toward the development of novel antiviral therapies, vaccines against human orthopoxvirus infections, new approaches for the environmental detection of virions, and methods to accomplish more rapid diagnosis of disease.

Proper citation: Poxvirus Bioinformatics Resource Center (RRID:SCR_007870) Copy   

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http://www.webcitation.org/getfile?fileid=c2cde11f2c71cfb474c58964754c6aecc7586986

NASCArrays is the Nottingham Arabidopsis Stock Centre''s microarray database. Currently most of the data is for Arabidopsis thaliana experiments run by the NASC Affymetrix Facility. There are also experiments from other species, and experiments run by other centres too. NASCArrays is an Affymetrix microarray database. It contains free Affymetrix microarray data, and also features a series of tools allowing you to query that data in powerful ways. Most of the data currently comes from NASC''s Affymetrix Service. It also includes data from other sources, notably the AtGenExpress project. They currently distribute over 30,000 tubes of seed a year. There are currently the following data mining tools available. All of these tools allow you to type in a gene(s) of interest, and identify experiments or slides that you might be interested in: -Spot History: This tool allows you to see the pattern of gene expression over all slides in the database. Easily identify slides (and therefore experimental treatments) where genes are highly, lowly, or unusually expressed -Two gene scatter plot: This tool allows you to see the pattern of gene expression over all slides for two genes as a scatter plot. If you are interested in two genes, you can find out if they act in tandem, and highlight slides (and therefore experimental conditions) where these two genes behave in an unusual manner. -Gene Swinger: If you have a gene of interest, this tool will show you which experiment the gene expression varied most -Bulk Gene Download: This tool allows you to download the expression of a list of genes over all experiments. You can get all genes over all experiments (the entire database!) from the Super Bulk Gene Download Sponsors: This is a BBSRC funded consortium to provide services to the Arabidopsis community.

Proper citation: NASCArrays: The Nottingham Arabidopsis Stock Centre Arrays (RRID:SCR_008126) Copy   

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http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

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http://www.biosci.ohio-state.edu/~plantbio/Facilities/abrc/abrchome.htm

The mission of the Arabidopsis Biological Resource Center (ABRC) is to acquire, preserve and distribute seed and DNA resources that are useful to the Arabidopsis research community. More than 100,000 stocks are shipped annually to researchers in more than 60 countries, and modest fees for stocks are charged. The ABRC database functions and ordering system are incorporated into The Arabidopsis Information Resource (TAIR). Researchers can obtain information about Arabidopsis, perform stock searches, order stocks, and view current and past orders. Sponsors: ABRC is supported by the National Science Foundation under Grant No. 0542034.

Proper citation: Arabidopsis Biological Resource Center (RRID:SCR_008136) Copy   

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http://www.qoscosgrid.eu/

Complex systems are defined as systems with many interdependent parts which give rise to non-linear and emergent properties determining the high-level functioning and behavior of such systems. Due to the interdependence of their constituent elements and other characteristics of complex systems, it is difficult to predict system behavior based on the sum of their parts alone. Examples of complex systems include bee hives, bees themselves, human economies and societies, nervous systems, molecular interactions, cells and living things, ecosystems, as well as modern energy or telecommunication infrastructures. Arguably one of the most striking properties of complex systems is that conventional experimental and engineering approaches are inadequate to capture and predict the behavior of such systems. To complement the conventional experimental and engineering approaches, computer-based simulations of complex natural phenomena and complex man-made artifacts are increasingly employed across a wide range of sectors. Typically, such simulations require computing environments which meet very high specifications in terms of processing units, primary and secondary storage, and communication. Supercomputers constitute the de facto technology to deliver the required specifications. Acquiring, operating and maintaining supercomputers involve considerable costs, which many organizations cannot afford. The working assumption of the QosCosGrid project is that a grid could be enhanced by suitable middleware to provide features and performance characteristics that resemble those of a supercomputer., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Quasi Opportunistic Supercomputing for Complex Systems (RRID:SCR_008542) Copy   

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http://fungi.ensembl.org/index.html

The Ensembl Genomes project produces genome databases for important species from across the taxonomic range, using the Ensembl software system. Five sites are now available, one of which is Ensembl Fungi, which houses fungal species. Sponsors: EnsembFungi is a project run by EMBL - EBI to maintain annotation on selected genomes, based on the software developed in the Ensembl project developed jointly by the EBI and the Wellcome Trust Sanger Institute.

Proper citation: Ensembl Fungi (RRID:SCR_008681) Copy   

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http://plants.ensembl.org/index.html

Ensembl Genomes project produces genome databases for important species from across the taxonomic range, using the Ensembl software system. Five sites are now available, one of which is Ensembl Plants, which houses plant species. Sponsors: EnsembPlants is a project run by EMBL - EBI to maintain annotation on selected genomes, based on the software developed in the Ensembl project developed jointly by the EBI and the Wellcome Trust Sanger Institute.

Proper citation: Ensembl Plants (RRID:SCR_008680) Copy   

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http://bacteria.ensembl.org/index.html

The Ensembl Genomes project produces genome databases for important species from across the taxonomic range, using the Ensembl software system. Five sites are now available, one of which is Ensembl Bacteria, which houses bacterial species. All bacterial collections in Ensembl Bacteria have been updated with the latest data from ENA and UniProtKB. New genomes have been added to Escherichia/Shigella (3 additional genomes) and Staphylococcus (3 additional genomes). The mapping of array probes has been expanded to all genomes in the Escherichia/Shigella and Staphylococcus collections. Ensembl Bacteria also now features improved interfaces for selecting regions of circular molecules a new visualisation allowing the large scale comparison of multiple genomes. In multi-synteny view, users can select multiple genomes and observe the syntenic relationships between them. Sponsors: EnsembBacteria is a project run by EMBL - EBI to maintain annotation on selected genomes, based on the software developed in the Ensembl project developed jointly by the EBI and the Wellcome Trust Sanger Institute.

Proper citation: Ensembl Bacteria (RRID:SCR_008679) Copy   

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http://www.phylo.org/sub_sections/portal/

This database is a public resource for inference of large phylogenetic trees. It is designed to provide all researchers with access to large computational resources of the NSF TeraGrid through a simple browser interface. The CIPRES Science Gateway provides new hybrid parallel versions of RAxML (7.2.7) and MrBayes (3.1.2), as well as parallel GARLI (1.0) code to insure the fastest possible run times for submitted jobs. Through a collaboration with Alexandros Stamatakis and Wayne Pfeiffer, they now offer the fastest hybrid versions of RAxML and MrBayes currently available. Sponsors: The CIPRES project is a multi-site collaboration funded by the NSF Information Technology Research (ITR) program grant entitled BUILDING THE TREE OF LIFE: A National Resource for Phyloinformatics and Computational Phylogenetics.

Proper citation: CIPRES Science Gateway (RRID:SCR_008439) Copy   

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http://research.nhgri.nih.gov/bic/

When the BRCA1 gene was cloned, a Steering Committee was initiated to help coordinate the formation of a Breast Cancer Information Core (BIC) that could act as such a central repository. NHGRI has chosen as the most accessible format for the BIC this World Wide Web site. The recent identification of mutations in breast cancer susceptibility genes has provided the exciting opportunity to help identify women who are at high risk to develop breast cancer. One of the serious impediments to achieving clinical benefits from this information however, is finding and assessing the significance of mutations in these new susceptibility genes. It is imperative that the detection and interpretation of these mutations is coordinated and that this information is made available to as many qualified investigators as possible. There are many sites on the web that contain general as well as scientific information relevant to breast cancer. A partial list of these can be found here. Having participated in the poorly coordinated analysis of other cancer susceptibility genes, we consider it important to create and maintain a central repository for information regarding mutations and polymorphisms. NHGRI also think it critical to make available the reagents necessary to carry out many different techniques for the detection of such mutations. Sponsors: This resource is supported by the National Human Genome Research Institute (NHGRI). Keywords: Breast, Cancer, Mutation, Clincial, Polymorphism, Gene, Scientific,

Proper citation: An Open Access On-Line Breast Cancer Mutation Data Base (RRID:SCR_008432) Copy   

•   Source: SciCrunch Registry