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http://www.cta.lncc.br/

A database of information about each Cancer-Testis (CT) gene, its gene products and the immune response induced in cancer patients by these proteins. CT antigens are proteins normally expressed only in the human germ line but that are also present in a significant subset of malignant tumors. The practical importance of these proteins is that due to their restricted expression pattern they are frequently recognized by the immune system of cancer patients. Moreover, this antigenicity has raised the possibility of their being used as vaccines to actively stimulate immune responses in order to combat tumor growth. As a result worldwide research into many aspects of CT antigens is rapidly growing prompting the construction of this database as a resource for investigators involved in this area.

Proper citation: CTDatabase (RRID:SCR_007614) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org

Blocks is a database of highly conserved regions of proteins, or Blocks. THe database is no longer maintained or updated and some of its tools are no longer functional. However, Blocks does provide Block Searcher, Get Blocks and Block Maker, aids to detection and verification of protein sequence homology. They compare a protein or DNA sequence to a database of protein blocks (current version), retrieve blocks, and create new blocks, respectively. Users can further view blocks by (keyword or number), search a sequence against the database of blocks, search blocks against each other, or make blocks of their own.

Proper citation: Blocks (RRID:SCR_007567) Copy   

•   Source: SciCrunch Registry

http://urgv.evry.inra.fr/CATdb

CATdb collects together all the information on transcriptome experiments done at URGV with CATMA micro arrays. All data in CATdb come from the URGV micro array platforms. Common procedures are used including any steps from the experiment design to the statistical analyses. Directed through a WEB interface, biologists enter the standard description of each experimental step (extraction, labelling, hybridization and scanning). Then, normalization and statistical analyses are done following a set of selected methods depending on the experimental design and array types.

Proper citation: CATdb: a Complete Arabidopsis Transcriptome database (RRID:SCR_007582) Copy   

•   Source: SciCrunch Registry

http://www.allelefrequencies.net

The main purpose of the allelefrequencies.net website is to provide one central source, freely available to all. For the storage of allele frequencies from different polymorphic areas in the HUMAN genome. Users can contribute the results of their work into one common database, and can perform database searches on information already available. They have currently collected data in allele, haplotype and genotype format. The success of this website will depend on you to contribute your data. Sponsors: This resource is supported Royal Liverpool University. Keywords: Allele, Polymorphic, Genome, Database, Data, Haplotype, Genotype,

Proper citation: Allele Frequencies in Worldwide Populations (RRID:SCR_007259) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/genenet/

Integrated system GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNet (RRID:SCR_007678) Copy   

•   Source: SciCrunch Registry

http://bite-it.helsinki.fi/

A database of gene expression in tooth. It includes expression information on the initiation, bud, cap, bell, differentiation, and secretory stages, as well as on root development. The website also examines epithelial layers, growth factors and receptors, signaling molecules and transcription factors.

Proper citation: Gene Expression in Tooth Database (RRID:SCR_007671) Copy   

•   Source: SciCrunch Registry

http://img.jgi.doe.gov/

Datasets and tools for comparative analysis and annotation of all publicly available genomes from three domains of life in a uniquely integrated context. Plasmids that are not part of a specific microbial genome sequencing project and phage genomes are also included in order to increase its genomic context for comparative analysis. The user interface (see User Interface Map) allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes.

Proper citation: IMG (RRID:SCR_007733) Copy   

•   Source: SciCrunch Registry

http://www.interfil.org

The Human Intermediate Filament Database is a continuously updated review of the intermediate filament field. It is hoped that users will contribute to the development and expansion of the database on a regular basis. Contributions may include novel variants, new patients with previously discovered sequence and allelic variants. Suggestions on ways to improve the database are also welcome. The entire database can be searched through the Browse and Search options. A number of different parameters can be used to search the database including unique identifier, intermediate filament, disease DNA variations, amino acid variations, domain, date accepted, author and abstract. Output from the search is returned in a table containing all the pertinent cross referenced information. Multiple sequence alignment can also be performed via the CLUSTALW program to determine cDNA or protein sequence conservation. The database is linked to multiple other resources including NCBI RefSeq, PDB, OMIM, UCSC genome browser, NCBI Gene, HomoloGene, PubMed and HGNC. In the case of HGNC, reciprocal links are also available from HGNC that links to Human Intermediate Filament Database. Due to the protein centric nature of the Human Intermediate Filament Database and the gene centric nature of HGNC, a HGNC record will potentially link to multiple records in this database due to the presence of alternative splicing. In such an event, the Human Intermediate Filament Database will present to the user a list of all the protein records resulting from the HGNC gene record. The database uses Jalview and Jmol applets for the visualization of multiple sequence alignment and structure respectively. The database contains information on disease phenotypes of a variety of different intermediate filament related diseases.

Proper citation: Human Intermediate Filament Database (RRID:SCR_007744) Copy   

•   Source: SciCrunch Registry

http://www.interferome.org

Interferome is a database that provides identification of interferon regulated gene signatures from high-throughput data sets (i.e. microarray, proteomic data etc.). It will also assist in identifying regulatory elements and enable comparison of tissue expression of IRGs in human and mouse. Availability of sequence information from more than 37 species, together with comprehensive annotation will enable comparative genomics and phylogenetic analysis to be performed on these IRGs. Within the database, Type I, II and III IFN regulated genes have been manually curated from more than 28 publicly available microarray datasets. Interferon Regulated Genes (IRGs) were identified from multiple microarray and proteomic experiments where cells were treated with IFNs. Genes that were up or down regulated more than 1.5 fold relative to control samples were defined as IRGs.

Proper citation: Interferome (RRID:SCR_007743) Copy   

•   Source: SciCrunch Registry

http://www.oreganno.org/oregano/

Open source, open access database and literature curation system for community based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. Automatically cross referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, eVOC: Cell type ontology, and Taxonomy database. Community driven resource for curated regulatory annotation.

Proper citation: Open Regulatory Annotation Database (RRID:SCR_007835) Copy   

•   Source: SciCrunch Registry

http://nematode.net/

The home page of the parasitic nematode EST project at Washington University's Genome Sequencing Center, St. Louis. It was established in 2000 as a component of the NIH-NIAID grant "A Genomic Approach to Parasites from the Phylum Nematoda."

Proper citation: Nematode.net (RRID:SCR_007816) Copy   

•   Source: SciCrunch Registry

http://phylomedb.bioinfo.cipf.es

Database for phylomes, that is, complete collections of phylogenetic trees for all proteins encoded in a given genome. It aims at providing a repository of high-quality phylogenies and alignments for proteins encoded in model species. To derive a phylome, each protein encoded in a given genome is used as a seed to retrieve its homologs in other complete genomes. These sequences are aligned and processed to derive reliable phylogenies using several phylogenetic methods. Besides providing the evolutionary history of the gene families, phylomeDB includes phylogeny based predictions of orthology and paralogy relationships., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhylomeDB (RRID:SCR_007850) Copy   

•   Source: SciCrunch Registry

http://www.panzea.org

It contains the genotype, phenotype, and polymorphism data produced by the NSF-funded project; Genetic Architecture of Maize and Teosinte. The PANZEA project will identify genes that control domestication traits and three key agronomic traits: flowering time, plant height, and kernel quality. Genetic linkage, association, and fine mapping analyses will be performed on the largest and most diverse set of mapping families publicly available for any species. A large series of isogenic lines will be used to characterize allelic series and epistatic interactions. The genetic architecture of each of the four trait groups will be compared and contrasted, and the influence of recombination and past domestication bottlenecks on the genomic distribution of functional diversity will be examined. Finally, the ability of genetic architecture-based models to predict phenotype will be evaluated in a broad range of germplasm, including elite US hybrids. This project will take a step toward the ultimate goal of predicting phenotype from genotype.

Proper citation: PANZEA (RRID:SCR_007846) Copy   

•   Source: SciCrunch Registry

http://www.shigen.nig.ac.jp/rice/oryzabase/

A comprehensive rice science database established in 2000 by rice researcher''s committee in Japan. The database is originally aimed to gather as much knowledge as possible ranging from classical rice genetics to recent genomics and from fundamental information to hot topics. The Oryzabase consists of five parts, (1) genetic resource stock information, (2) gene dictionary, (3) chromosome maps, (4) mutant images, and (5) fundamental knowledge of rice science. We are planning to do more extensive cross-referencing of Oryzabase to the major DNA sequence database, literature database and other plant databases in order to provide the wealth of information to rice researchers. We are calling for additional mutants and mapped gene information to incorporate into the Oryzabase. Newly identified mutants and mapped trait genes published in the scientific journals will be welcome to integrate into the Oryzabase maps.

Proper citation: Oryzabase (RRID:SCR_007840) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry