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http://www.flyprot.org/

Allows annotation of gene expression at all stages of development and tissue types (including sub cellular location) using standard Drosophila anatomy ontology. All methods of input use a controlled vocabulary to ensure data integrity.

Proper citation: Flannotator (RRID:SCR_001608) Copy   

•   Source: SciCrunch Registry

http://caps.ncbs.res.in/stifdb2/

Database of biotic and abiotic stress responsive genes in Arabidopsis thaliana and Oryza sativa L. with options to identify probable Transcription Factor Binding Sites in their promoters. In the response to biotic stress like Bacteria and abiotic stresses like ABA, drought, cold, salinity, dehydration, UV-B, high light, heat,heavy metals etc, ten specific families of transcription factors in Arabidopsis thaliana and six in Oryza sativa L. are known to be involved. HMM-based models are used to identify binding sites of transcription factors belonging to these families. They have also consulted literature reports to cross-validate the Transcription Factor Binding Sites predicted by the method.

Proper citation: STIFDB (RRID:SCR_002131) Copy   

•   Source: SciCrunch Registry

http://pathway.gramene.org/gramene/ricecyc.shtml

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. RiceCyc is a catalog of known and/or predicted biochemical pathways from rice (Oryza sativa). Pathways and genes presented in this catalog are primarily based on the annotations carried out by Gramene database project on the release 5 of the TIGR-assembly of Oryza sativa japonica cv. Nipponbare genome sequenced by IRGSP.

Proper citation: Rice Metabolic Pathway Database (RRID:SCR_002128) Copy   

•   Source: SciCrunch Registry

http://pstiing.icr.ac.uk/

A publicly accessible knowledgebase about protein-protein, protein-lipid, protein-small molecules, ligand-receptor interactions, receptor-cell type information, transcriptional regulatory and signal transduction modules relevant to inflammation, cell migration and tumourigenesis. It integrates in-house curated information from the literature, biochemical experiments, functional assays and in vivo studies, with publicly available information from multiple and diverse sources across human, rat, mouse, fly, worm and yeast. The knowledgebase allowing users to search and to dynamically generate visual representations of protein-protein interactions and transcriptional regulatory networks. Signalling and transcriptional modules can also be displayed singly or in combination. This allow users to identify important "cross-talks" between signalling modules via connections with key components or "hubs". The knowledgebase will facilitate a "systems-wide" understanding across many protein, signalling and transcriptional regulatory networks triggered by multiple environmental cues, and also serve as a platform for future efforts to computationally and mathematically model the system behavior of inflammatory processes and tumourigenesis.

Proper citation: pSTIING (RRID:SCR_002045) Copy   

•   Source: SciCrunch Registry

http://cmbi.bjmu.edu.cn/mirsnp

Database of human SNPs in predicted miRNA-mRNA binding sites, based on information from dbSNP135 and mirBASE18. MirSNP is highly sensitive and covers most experiments confirmed SNPs that affect miRNA function. MirSNP may be combined with researchers' own GWAS or eQTL positive data sets to identify the putative miRNA-related SNPs from traits/diseases associated variants. They aim to update the MirSNP database as new versions of mirBASE and dbSNP database become available.

Proper citation: MirSNP (RRID:SCR_001629) Copy   

•   Source: SciCrunch Registry

https://gtexportal.org/home/

Database and browser that provides a central resource to archive and display association between genetic variation and high-throughput molecular-level phenotypes. This effort originated with the NIH GTEx roadmap project: however the scope of this resource will be extended to include any available genotype/molecular phenotype datasets.

Proper citation: GTEx eQTL Browser (RRID:SCR_001618) Copy   

•   Source: SciCrunch Registry

http://giladlab.uchicago.edu/orthoExon/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of orthologous exon regions in the genomes of human, chimpanzee, and rhesus macaque. It can be used in analysis of multi-species RNA-seq expression data, allowing for comparisons of exon-level expression across primates, as well as comparative examination of alternative splicing and transcript isoforms.

Proper citation: Primate Orthologous Exon Database (RRID:SCR_002065) Copy   

•   Source: SciCrunch Registry

http://atgc.lbl.gov/atgc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. ATGC stands for Alignable Tight Genomic Cluster, which is cluster of closely related prokaryotic genomes. ATGC is the principal notion of this web resource. The purpose of this web resource is to prepare ATGC-derived data sets for a variety of research projects in functional and evolutionary genomics. Unique features of ATGC include: * Reliable identification of orthologs (high degree of similarity between the genomes in the set allow an extensive use of synteny in ortholog identification); * Fine granularity of protein classification (in comparisons of more distant genomes, proteins belonging to families of paralogs are often lumped into a singlegroup; under the ATGC approach, comparison of genomic sequences from highly similar genomes allows one to track each set of orthologs separately); * Relative rarity of changes of any kind (in sequence, genome organization and gene content) allows the use of parsimony-related methods of analysis.

Proper citation: Alignable Tight Genomic Cluster (RRID:SCR_001894) Copy   

•   Source: SciCrunch Registry

http://www.pubgene.org/

It helps users retrieve information on genes and proteins. The underlying structure of PubGene can be viewed as a gene-centric database. Gene and protein names are cross-referenced to each other and to terms that are relevant to understanding their biological function, importance in disease and relationship to chemical substances. The result is a literature network organizing information in a form that is easy to navigate.

Proper citation: PubGene (RRID:SCR_002119) Copy   

•   Source: SciCrunch Registry

http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-8-335

Cell signaling pathways can be explored using PathFinder, the interactive, online graphical representation of cell signaling pathways. The user can use PathFinder to explore the relationships between different cell signaling pathway components while being presented with our high quality small molecules, antibodies, enzymes, siRNA for gene knockdown and qPCR components to aid them in their research.

Proper citation: Cell Signaling Pathways (RRID:SCR_002070) Copy   

•   Source: SciCrunch Registry

http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/swissprot/hpi/hpi.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 03, 2011. IT HAS BEEN REPLACED BY A NEW UniProtKB/Swiss-Prot ANNOTATION PROGRAM CALLED UniProt Chordata protein annotation program. The Human Proteome Initiative (HPI) aims to annotate all known human protein sequences, as well as their orthologous sequences in other mammals, according to the quality standards of UniProtKB/Swiss-Prot. In addition to accurate sequences, we strive to provide, for each protein, a wealth of information that includes the description of its function, domain structure, subcellular location, similarities to other proteins, etc. Although as complete as currently possible, the human protein set they provide is still imperfect, it will have to be reviewed and updated with future research results. They will also create entries for newly discovered human proteins, increase the number of splice variants, explore the full range of post-translational modifications (PTMs) and continue to build a comprehensive view of protein variation in the human population. The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focused on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering, proteome analysis can now be provided in a meaningful way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry. We maintain a file containing all human UniProtKB/Swiss-Prot entries. This file is updated at every biweekly release of UniProt and can be downloaded by FTP download, HTTP download or by using a mirroring program which automatically retrieves the file at regular intervals.

Proper citation: Human Proteomics Initiative (RRID:SCR_002373) Copy   

•   Source: SciCrunch Registry

http://www.ecoli-york.org/

A database that curates new experimental and bioinformatic information about the genes and gene products of the model bacterium Escherichia coli K-12 strain MG1655. It has been created to integrate information from post-genomic experiments into a single resource with the aim of providing functional predictions for the 1500 or so gene products for which we have no knowledge of their physiological function. While EchoBASE provides a basic annotation of the genome, taken from other databases, its novelty is in the curation of post-genomic experiments and their linkage to genes of unknown function. Experiments published on E. coli are curated to one of two levels. Papers dealing with the determination of function of a single gene are briefly described, while larger dataset are actually included in the database and can be searched and manipulated. This includes data for proteomics studies, protein-protein interaction studies, microarray data, functional genomic approaches (looking at multiple deletion strains for novel phenotypes) and a wide range of predictions that come out of in silico bioinformatic approaches. The aim of the database is to provide hypothesis for the functions of uncharacterized gene products that may be used by the E. coli research community to further our knowledge of this model bacterium.

Proper citation: EchoBASE (RRID:SCR_002430) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/ieb/research/acembly/

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., documented August 29, 2016. AceView offers an integrated view of the human, nematode and Arabidopsis genes reconstructed by co-alignment of all publicly available mRNAs and ESTs on the genome sequence. Our goals are to offer a reliable up-to-date resource on the genes and their functions and to stimulate further validating experiments at the bench. AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals' transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated. Our goals are to offer an up-to-date resource on the genes, in the hope to stimulate further experiments at the bench, or to help medical research. AceView can be queried by meaningful words or groups of words as well as by most standard identifiers, such as gene names, Entrez Gene ID, UniGene ID, GenBank accessions.

Proper citation: AceView (RRID:SCR_002277) Copy   

•   Source: SciCrunch Registry

https://enigma.lbl.gov/regprecise/

Collection of manually curated inferences of regulons in prokaryotic genomes. Database for capturing, visualization and analysis of transcription factor regulons that were reconstructed by comparative genomic approach in wide variety of prokaryotic genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RegPrecise (RRID:SCR_002149) Copy   

•   Source: SciCrunch Registry

http://www.angis.org.au/Databases/Heart/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The aim of this locus-specific mutation database was to provide an online resource that contains summarized and updated information on familial hypertrophic cardiomyopathy (FHC)-associated mutations and related data, for researchers and clinicians. It also serves as a means of publishing previously unpublished data, which could be of value in understanding genotype/phenotype correlations. This database contains mutations in various genes known to cause familial hypertrophic cardiomyopathy, a genetic disorder associated with defects in the sarcomere [1]. Only gene symbols approved by HUGO are used and mutations are reported in accordance with guidelines recommended by the Mutation Database Initiative of HUGO and EBI.

Proper citation: Familial Hypertrophic Cardiomyopathy DNA Mutation Database (RRID:SCR_002346) Copy   

•   Source: SciCrunch Registry

http://dbtbs.hgc.jp/

Database of experimentally validated gene regulatory relations and the corresponding transcription factor binding sites upstream of Bacillus subtilis genes. The database allows the comparison of systematic experiments with individual experimental results in order to facilitate the elucidation of the complete B. subtilis gene regulatory network. The current version is constructed by surveying 947 references and contains the information of 120 binding factors and 1475 gene regulatory relations. For each promoter, all of its known cis-elements are listed according to their positions, while these cis-elements are aligned to illustrate the consensus sequence for each transcription factor. All probable transcription factors coded in the genome were classified using Pfam motifs. The DBTBS database was reorganized to show operons instead of individual genes as the building blocks of gene regulatory networks. It now contains 463 experimentally known operons, as well as their terminator sequences if identifiable. In addition, 517 transcriptional terminators were identified computationally. (De Hoon, M.J.L. et al., PLoS Comput. Biol. 1, e25 (2005)). A new section was added under "Motif conservation", which presents hexameric motifs found to be conserved to different extents between upstream intergenic regions of genus-specific subgroups of homologous proteins.

Proper citation: DBTBS (RRID:SCR_002345) Copy   

•   Source: SciCrunch Registry

http://eggnog.embl.de

A database of orthologous groups of genes. The orthologous groups are annotated with functional description lines (derived by identifying a common denominator for the genes based on their various annotations), with functional categories (i.e derived from the original COG/KOG categories). eggNOG's database currently counts 1.7 million orthologous groups in 3686 species, covering over 7.7 million proteins (built from 9.6 million proteins). (Jan 30, 2014)

Proper citation: eggNOG (RRID:SCR_002456) Copy   

•   Source: SciCrunch Registry

http://edas2.bioinf.fbb.msu.ru/

Databases of alternatively spliced genes with data on the alignment of proteins, mRNAs, and EST. It contains information on all exons and introns observed, as well as elementary alternatives formed from them. The database makes it possible to filter the output data by changing the cut-off threshold by the significance level. It contains splicing information on human, mouse, dog (not yet functional) and rat (not yet functional). For each database, users can search by keyword or by overall gene expression. They can also view genes based on chromosomal arrangement or other position in genome (exon, intron, acceptor site, donor site), functionality, position, conservation, and EST coverage. Also offered is an online Fisher test.

Proper citation: EDAS - EST-Derived Alternative Splicing Database (RRID:SCR_002449) Copy   

•   Source: SciCrunch Registry

http://cpdb.molgen.mpg.de

An integrative interaction database that integrates different types of functional interactions from heterogeneous interaction data resources. Physical protein interactions, metabolic and signaling reactions and gene regulatory interactions are integrated in a seamless functional association network that simultaneously describes multiple functional aspects of genes, proteins, complexes, metabolites, etc. With human, yeast and mouse complex functional interactions, it currently constitutes the most comprehensive publicly available interaction repository for these species. Different ways of utilizing these integrated interaction data, in particular with tools for visualization, analysis and interpretation of high-throughput expression data in the light of functional interactions and biological pathways is offered.

Proper citation: ConsensusPathDB (RRID:SCR_002231) Copy   

•   Source: SciCrunch Registry