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

Archive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.

Proper citation: ClinVar (RRID:SCR_006169) Copy   

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http://c1.accurascience.com/miRecords/

A resource for animal miRNA-target interactions consisting of the Validated Targets component, a large, high-quality database of experimentally validated miRNA targets resulting from meticulous literature curation, and the Predicted Targets component, an integration of predicted miRNA targets produced by 11 established miRNA target prediction programs. April 27, 2013, the Validated Targets component of miRecords hosts 2705 records of interactions between 644 miRNAs and 1901 target genes in 9 animal species. Among these records, 2028 were curated from low throughput experiments. The Predicted Targets component of mIRecords integrates the predicted targets of the following miRNA target prediction tools: DIANA-microT, MicroInspector, miRanda, MirTarget2, miTarget, NBmiRTar, PicTar, PITA, RNA22, RNAhybrid, and TargetScan/TargertScanS. We would be glad to include your experimentally validated miRNA target data (published or unpublished) into miRecords., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: miRecords (RRID:SCR_013021) Copy   

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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   

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http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

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http://floresta.eead.csic.es/footprintdb/index.php

Database with 2797 unique DNA-binding proteins (mostly transcription factors, TFs), 4196 Position Weight Matrices (PWMs) and 13161 DNA Binding Sites extracted from the literature and other repositories. The binding interfaces of (most) proteins in the database are inferred from the collection of protein-DNA complexes described in 3D-footprint. The database predicts transcription factors which bind a specific DNA site or motif and DNA motifs or sites likely to be recognized by a specific DNA-binding protein.

Proper citation: footprintDB (RRID:SCR_005368) Copy   

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http://dbserv2.informatik.uni-leipzig.de:8080/onex/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Web-based application that integrates versions of 16 life science ontologies including the Gene Ontology, NCI Thesaurus and selected OBO ontologies with data leading back to 2002 in a common repository to explore ontology changes. It allows to study and apply the evolution of these integrated ontologies on three different levels. It provides global ontology evolution statistics and ontology-specific evolution trends for concepts and relationships and it allows the migration of annotations in case a new ontology version was released

Proper citation: OnEx - Ontology Evolution Explorer (RRID:SCR_000602) Copy   

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http://www.genomesunzipped.org/

A group blog providing expert, independent commentary on the personal genomics industry. The goal of the project is to provide genetic testing consumers with independent and informed analysis of developments in the field of genetics and the genetic testing industry. Members of Genomes Unzipped include active researchers in various fields of genetics, as well as specialists in the legal and public health issues surrounding new genomic technologies. Many of us have also been extensively involved in public communication about genetics. Members of the group have had their DNA tested with a variety of products. We have released all of these genetic data openly to the public, both as raw data and in a custom genome browser. As the project proceeds we plan to obtain more genetic tests ����?? up to and including whole genome sequencing ����?? and to continue to release these data to the world. The group is also performing analyses of our own raw genetic data to illustrate fundamental concepts in genetics, using software written both by group members and other collaborators; and we����??ll be releasing the code for that software in our new code repository. As the project expands, we����??ll be looking to add data from other volunteers to the project, as well as to collaborate with other ����??genome hackers����?? on the development of new tools for exploring genetic data.

Proper citation: Genomes Unzipped (RRID:SCR_006870) Copy   

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http://www.psidev.info/

Initiative to define community standards for data representation in proteomics to facilitate data comparison, exchange and verification. The main organizational unit is the work group, with a Gel Electrophoresis (GEL) work group, a Mass Spectrometry (MS) work group, a Molecular Interactions (MI) work group, a Protein Modifications (MOD) work group, a Proteomics Informatics (PI) work group, and a Sample Processing (SP) work group. The Gel Electrophoresis (GEL) work group aims to develop reporting requirements that supplement the Minimum Information About a Proteomics Experiment (MIAPE) parent document, describing the minimum information that should be reported about gel-based experimental techniques used in proteomics. The group will also develop data formats for capturing MIAPE-compliant data about gel electrophoresis and informatics performed on gel images. The Mass Spectrometry Standards Working Group defines community data formats and controlled vocabulary terms facilitating data exchange and archiving in the field of proteomics mass spectrometry. A past achievement is the mzData standard, which captures mass spectrometry output data. mzData's aim is to unite the large number of current formats (pkl's, dta's, mgf's, .....) into a single format. mzData has been released but is now deprecated in favor of mzML. The Molecular Interactions workgroup is concentrating on improving the annotation and representation of molecular interaction data wherever it is published, be this in journal articles, authors web-sites or public domain databases; and improving the accessibility of molecular interaction data to the user community. By using a common standard data can be downloaded from multiple sources and easily combined using a single parser. The protein modification workgroup focuses on developing a consensus nomenclature and provide an ontology reconciling in a hierarchical representation the complementary descriptions of residue modifications. The protein modification ontology (PSI-MOD) is available in OBO format or in OBO.xml. A spreadsheet containing the mapping of the descriptive labels used in various databases and search engines, the consensus list of proposed short name for protein modifications established by collaborative effort of mass spectrometry community, and the proposed rules and recommendations for this nomenclature are available. These short names are included in the ontology as synonyms of the corresponding terms. The Proteomics Informatics Standards Group (PSI-PI) goals are to provide a set of minimal reporting requirements which augment the MIAPE reporting guidelines with respect to analysis of data derived from proteomics experiments; to provide vendor-neutral and standard formats for representing results of analyzing and processing experimental data; to foster adoption of the format by highlighting efforts made by vendors and individuals that utilize the format in their products. The remit of the Sample Processing Working Group is to produce reporting guidelines, data exchange formats and controlled vocabulary covering all separation techniques not considered to be "classical" one- or two-dimensional gel electrophoresis (cf. the Gel WG home page), along with other kinds of sample handling and processing (for example, "tagging" proteins or peptides, splitting, combining and storing samples). Where possible we seek to develop our products in collaboration with all proteomics stakeholders and, where relevant, developers from other standards communities, most notably metabolomics. * Minimum reporting requirements: The evolving Minimum Information About a Proteomics Experiment (MIAPE) documents offer guidelines on how to adequately report a proteomics experiment. It is expected that these documents will be published, and that the requirements within will be enforced by journals, compliant repositories and funders (cf. MIAME). * XML formats for data exchange: Derived from the FuGE general object model, the formats developed by this workgroup are designed to function both as standalone files and as part of a "parent" FuGE-ML document. These formats will facilitate data exchange between researchers, and submission to repositories or journals. * Controlled vocabularies (CVs) and ontology: Lists of clearly defined terms are crucial for the construction of unambiguously worded data files. In addition to providing supporting CVs for the individual data capture formats as part of the integrated PSI CV, the Sample Processing WG will contribute terms to the Functional Genomics Ontology (FuGO).

Proper citation: HUPO Proteomics Standards Initiative (RRID:SCR_003158) Copy   

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http://www.antibodypedia.com/

Open-access database of antibodies against human proteins developed through collaboration between Antibodypedia AB and the Nature Publishing Group. It aims to provide the scientific community and antibody distributors alike with information on the effectiveness of specific antibodies in specific applications--to help scientists select the right antibody for the right application. Antibodypedia's mission is to promote the functional understanding of the human proteome and expedite analysis of potential biomarkers discovered through clinical efforts. To this end, they have developed an open-access, curated, searchable database containing annotated and scored affinity reagents to aid users in selecting antibodies tailored to specific biological and biomedical assays. They envisage Antibodypedia as a virtual repository of validated antibodies against all human, and ultimately most model-organism, proteins. Such a tool will be exploitable to identify affinity reagents to document protein expression patterns in normal and pathological states and to purify proteins alone and in complex for structural and functional analyses. They hope to promote characterization of the roles and interplay of proteins and complexes in human health and disease. They encourage commercial providers to submit information regarding their inventory of antibodies with links to quality control data. Independent users can submit their own application-specific experimental data using standard validation criteria (supportive or non-supportive) developed with the assistance of an international advisory board recruited from academic research institutions. Users can also comment on specific antibodies without submitting validation data.

Proper citation: Antibodypedia (RRID:SCR_012782) Copy   

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http://www.yeastract.com

A curated repository of more than 206000 regulatory associations between transcription factors (TF) and target genes in Saccharomyces cerevisiae, based on more than 1300 bibliographic references. It also includes the description of 326 specific DNA binding sites shared among 113 characterized TFs. Further information about each Yeast gene has been extracted from the Saccharomyces Genome Database (SGD). For each gene the associated Gene Ontology (GO) terms and their hierarchy in GO was obtained from the GO consortium. Currently, YEASTRACT maintains a total of 7130 terms from GO. The nucleotide sequences of the promoter and coding regions for Yeast genes were obtained from Regulatory Sequence Analysis Tools (RSAT). All the information in YEASTRACT is updated regularly to match the latest data from SGD, GO consortium, RSA Tools and recent literature on yeast regulatory networks. YEASTRACT includes DISCOVERER, a set of tools that can be used to identify complex motifs found to be over-represented in the promoter regions of co-regulated genes. DISCOVERER is based on the MUSA algorithm. These algorithms take as input a list of genes and identify over-represented motifs, which can then be compared with transcription factor binding sites described in the YEASTRACT database.

Proper citation: Yeast Search for Transcriptional Regulators And Consensus Tracking (RRID:SCR_006076) Copy   

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http://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

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http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

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

Database containing descriptions of biological source materials used in experimental assays. Sources include: GenBank, Sequence Read Archive (SRA), Coriell, ATCC. Submissions are supported by a web-based Submission Portal that guides users through a series of forms for input of rich metadata describing their samples. As the capacity and complexity of biological data sets expands, databases face new challenges in ensuring that the information is adequately organized and described. The NCBI BioSample database is being developed to help address the challenges by providing the means by which data generators can organize and describe a broad range of sample types, and link to corresponding sets of experimental data in archival databases.

Proper citation: NCBI BioSample (RRID:SCR_004854) Copy   

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http://netbio.bgu.ac.il/tissuenet/

Database of human tissue protein-protein interactions (PPIs) that associates each interaction with human tissues that express both pair mates. This was achieved by integrating current data of experimentally detected PPIs with extensive data of gene and protein expression across 16 main human tissues. Users can query TissueNet using a protein and retrieve its PPI partners per tissue, or using a PPI and retrieve the tissues expressing both pair mates. The graphical representation of the output highlights tissue-specific and tissue-wide PPIs. Thus, TissueNet provides a unique platform for assessing the roles of human proteins and their interactions across tissues.

Proper citation: TissueNet - The Database of Human Tissue Protein-Protein Interactions (RRID:SCR_002052) Copy   

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http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

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