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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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3D Ribosomal Modification Maps Database Resource Report Resource Website 1+ mentions |
3D Ribosomal Modification Maps Database (RRID:SCR_003097) | 3D rRNA modification maps | data or information resource, database | Database of maps showing the sites of modified rRNA nucleotides. Access to the rRNA sequences, secondary structures both with modification sites indicated, 3D modification maps and the supporting tables of equivalent nucleotides for rRNA from model organisms including yeast, arabidopsis, e. coli and human is provided. This database complements the Yeast snoRNA Database at UMass-Amherst and relies on linking to some content from that database, as well as to others by colleagues in related fields. Therefore, please be very cognizant as to the source when citing information obtained herein. Locations of modified rRNA nucleotides within the 3D structure of the ribosome. | human, plant, arabidopsis, ribosome, eukaryote, eubacteria, archaea, eukarya |
is related to: Yeast snoRNA Database has parent organization: University of Massachusetts Amherst; Massachusetts; USA |
U.S. Public Health Service ; NIGMS GM19351 |
PMID:17947322 | Free, Freely available | nif-0000-00552 | SCR_003097 | 2026-02-11 10:56:38 | 2 | ||||||
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MITOMAP - A human mitochondrial genome database Resource Report Resource Website 100+ mentions |
MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) | MITOMAP | data or information resource, database | Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf. | gene, genome, diabetes, disease, disease-association, high resolution screening, human, inversion, metabolism, mitochondrial dna, mutation, phenotype, polymorphism, polypeptide assignment, pseudogene, restriction site, rna, sequence, trna, unpublished, variation, mitochondria, dna, insertion, deletion, FASEB list |
is used by: HmtVar is listed by: OMICtools is related to: Hereditary Hearing Loss Homepage has parent organization: Childrens Hospital of Philadelphia - Research Institute; Pennsylvania; USA has parent organization: Emory University School of Medicine; Atlanta; Georgia; USA |
NIH ; Muscular Dystrophy Foundation ; Ellison Foundation ; Diputacion General de Aragon Grupos consolidados B33 ; NIGMS GM46915; NINDS NS21328; NHLBI HL30164; NIA AG10130; NIA AG13154; NINDS NS213L8; NHLBI HL64017; NIH Biomedical Informatics Training Grant T15 LM007443; NSF EIA-0321390; Spanish Fondo de Investigacion Sanitaria PI050647; Ciber Enfermedades raras CB06/07/0043 |
PMID:17178747 PMID:15608272 PMID:9399813 PMID:9016535 PMID:8594574 |
Except where otherwise noted, Creative Commons Attribution License, The community can contribute to this resource | nif-0000-00511, OMICS_01641 | SCR_002996 | 2026-02-11 10:56:36 | 368 | ||||||
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PolymiRTS Resource Report Resource Website 100+ mentions |
PolymiRTS (RRID:SCR_003389) | PolymiRTS | data or information resource, database | Database of naturally occurring DNA variations in microRNA (miRNA) seed regions and miRNA target sites. MicroRNAs pair to the transcripts of protein-coding genes and cause translational repression or mRNA destabilization. SNPs and INDELs in miRNAs and their target sites may affect miRNA-mRNA interaction, and hence affect miRNA-mediated gene repression. The PolymiRTS database was created by scanning 3'UTRs of mRNAs in human and mouse for SNPs and INDELs in miRNA target sites. Then, the potential downstream effects of these polymorphisms on gene expression and higher-order phenotypes are identified. Specifically, genes containing PolymiRTSs, cis-acting expression QTLs, and physiological QTLs in mouse and the results of genome-wide association studies (GWAS) of human traits and diseases are linked in the database. The PolymiRTS database also includes polymorphisms in target sites that have been supported by a variety of experimental methods and polymorphisms in miRNA seed regions. | polymorphism, microrna, human, disease, trait, snp, indel, pathway, genetic variant, gene expression, phenotype, chromosome, chromosome location, bio.tools, FASEB list |
is listed by: OMICtools is listed by: bio.tools is listed by: Debian has parent organization: University of Tennessee Health Science Center; Tennessee; USA |
PhRMA Foundation ; UT Center for Integrative and Translational Genomics ; NICHD HD052472; NIAAA AA014425; NIDA DA021131; NINR NR009270; NIAID AI081050; NIAID AI019782; American Heart Association 0830134N; United States Department of Defense W81XHW-05-01-0227 |
PMID:24163105 PMID:22080514 |
Free, Available for download, Freely available | nif-0000-03324, biotools:polymirts, OMICS_00391 | https://bio.tools/polymirts | http://compbio.utmem.edu/miRSNP/ | SCR_003389 | Polymorphism in microRNA Target Site, PolymiRTS Database, Polymorphism in microRNAs and their TargetSites | 2026-02-11 10:56:43 | 149 | |||
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Rat Gene Symbol Tracker Resource Report Resource Website 10+ mentions |
Rat Gene Symbol Tracker (RRID:SCR_003261) | RGST | data or information resource, database | 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 September 2, 2016. Database for defining official rat gene symbols. It includes rat gene symbols from three major sources: the Rat Genome Database (RGD), Ensembl, and NCBI-Gene. All rat symbols are compared with official symbols from orthologous human genes as specified by the Human Gene Nomenclature Committee (HGNC). Based on the outcome of the comparisons, a rat gene symbol may be selected. Rat symbols that do not match a human ortholog undergo a strict procedure of comparisons between the different rat gene sources as well as with the Mouse Genome Database (MGD). For each rat gene this procedure results in an unambiguous gene designation. The designation is presented as a status level that accompanies every rat gene symbol suggested in the database. The status level describes both how a rat symbol was selected, and its validity. Rat Gene Symbol Tracker approves rat gene symbols by an automatic procedure. The rat genes are presented with links to RGD, Ensembl, NCBI Gene, MGI and HGNC. RGST ensures that each acclaimed rat gene symbol is unique and follows the guidelines given by the RGNC. To each symbol a status level associated, describing the gene naming process. | gene, orthology, naming, gene symbol, nomenclature, human, mouse |
is related to: Rat Genome Database (RGD) is related to: Entrez Gene is related to: Ensembl is related to: Mouse Genome Informatics (MGI) is related to: HGNC has parent organization: RatMap |
Swedish MRC ; Nilsson-Ehle Foundation ; Sven and Lilly Lawski Foundation ; Erik Philip-Sorensen Foundation ; Wilhelm and Martina Lundgren Research Foundation ; SWEGENE Foundation |
PMID:18215257 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-31426 | SCR_003261 | RGST (Rat Gene Symbol Tracker), RGST - Rat Gene Symbol Tracker | 2026-02-11 10:56:38 | 14 | |||||
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ASAP: the Alternative Splicing Annotation Project Resource Report Resource Website 10+ mentions |
ASAP: the Alternative Splicing Annotation Project (RRID:SCR_003415) | ASAP | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on 8/12/13. Database to access and mine alternative splicing information coming from genomics and proteomics based on genome-wide analyses of alternative splicing in human (30 793 alternative splice relationships found) from detailed alignment of expressed sequences onto the genomic sequence. ASAP provides precise gene exon-intron structure, alternative splicing, tissue specificity of alternative splice forms, and protein isoform sequences resulting from alternative splicing. They developed an automated method for discovering human tissue-specific regulation of alternative splicing through a genome-wide analysis of expressed sequence tags (ESTs), which involves classifying human EST libraries according to tissue categories and Bayesian statistical analysis. They use the UniGene clusters of human Expressed Sequence Tags (ESTs) to identify splices. The UniGene EST's are clustered so that a single cluster roughly corresponds to a gene (or at least a part of a gene). A single EST represents a portion of a processed (already spliced) mRNA. A given cluster contains many ESTs, each representing an outcome of a series of splicing events. The ESTs in UniGene contain the different mRNA isoforms transcribed from an alternatively spliced gene. They are not predicting alternative splicing, but locating it based on EST analysis. The discovered splices are further analyzed to determine alternative splicing events. They have identified 6201 alternative splice relationships in human genes, through a genome-wide analysis of expressed sequence tags (ESTs). Starting with 2.1 million human mRNA and EST sequences, they mapped expressed sequences onto the draft human genome sequence and only accepted splices that obeyed the standard splice site consensus. After constructing a tissue list of 46 human tissues with 2 million human ESTs, they generated a database of novel human alternative splices that is four times larger than our previous report, and used Bayesian statistics to compare the relative abundance of every pair of alternative splices in these tissues. Using several statistical criteria for tissue specificity, they have identified 667 tissue-specific alternative splicing relationships and analyzed their distribution in human tissues. They have validated our results by comparison with independent studies. This genome-wide analysis of tissue specificity of alternative splicing will provide a useful resource to study the tissue-specific functions of transcripts and the association of tissue-specific variants with human diseases. | gene, genome, human, isoform, mechanism, metazoa, molecular, mrna, nucleus, process, protein, sequence, splice, tissue specificity, transcription, transcript, alternate splicing, microarray, alternative splicing, biological process, alternatively spliced isoform, contig, cancer, image |
is listed by: Biositemaps is related to: Alternative Splicing Annotation Project II Database has parent organization: University of California at Los Angeles; California; USA |
NSF 0082964; NSF DGE-9987641; DOE DEFG0387ER60615 |
PMID:12519958 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-33105 | SCR_003415 | Alternative Splicing, Alternative Splicing Annotation Project, Alternative Splicing Annotation Project database | 2026-02-11 10:56:44 | 33 | |||||
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HapMap 3 and ENCODE 3 Resource Report Resource Website 1+ mentions |
HapMap 3 and ENCODE 3 (RRID:SCR_004563) | HapMap 3 and ENCORE 3 | data or information resource, database | Draft release 3 for genome-wide SNP genotyping and targeted sequencing in DNA samples from a variety of human populations (sometimes referred to as the HapMap 3 samples). This release contains the following data: * SNP genotype data generated from 1184 samples, collected using two platforms: the Illumina Human1M (by the Wellcome Trust Sanger Institute) and the Affymetrix SNP 6.0 (by the Broad Institute). Data from the two platforms have been merged for this release. * PCR-based resequencing data (by Baylor College of Medicine Human Genome Sequencing Center) across ten 100-kb regions (collectively referred to as ENCODE 3) in 712 samples. Since this is a draft release, please check this site regularly for updates and new releases. The HapMap 3 sample collection comprises 1,301 samples (including the original 270 samples used in Phase I and II of the International HapMap Project) from 11 populations, listed below alphabetically by their 3-letter labels. Five of the ten ENCODE 3 regions overlap with the HapMap-ENCODE regions; the other five are regions selected at random from the ENCODE target regions (excluding the 10 HapMap-ENCODE regions). All ENCODE 3 regions are 100-kb in size, and are centered within each respective ENCODE region. The HapMap 3 and ENCORE 3 data are downloadable from the ftp site. | human, gene, genotype, sequence, single nucleotide polymorphism, dna, software |
is listed by: 3DVC is related to: NHGRI Sample Repository for Human Genetic Research has parent organization: Baylor University; Texas; USA |
Wellcome Trust ; NHGRI ; NIDCD |
nlx_143820 | http://www.hgsc.bcm.tmc.edu/project-medseq-hm-hapmap3encode3.hgsc?pageLocation=hapmap3encode3 | SCR_004563 | 2026-02-11 10:56:55 | 3 | |||||||
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Collecting Duct Database Resource Report Resource Website |
Collecting Duct Database (RRID:SCR_000759) | CDDB | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This database is intended to serve as a learning tool to obtain curated information for the design of microarray targets to scan collecting duct tissues (human, rat, mouse). The database focuses on regulatory and transporter proteins expressed in the collecting duct, but when collecting duct proteins are a member of a larger family of proteins, common additional members of the family are included even if they have not been demonstrated to be expressed in the collecting duct. An Internet-accessible database has been devised for major collecting duct proteins involved in transport and regulation of cellular processes. The individual proteins included in this database are those culled from literature searches and from previously published studies involving cDNA arrays and serial analysis of gene expression (SAGE). Design of microarray targets for the study of kidney collecting duct tissues is facilitated by the database, which includes links to curated base pair and amino acid sequence data, relevant literature, and related databases. Use of the database is illustrated by a search for water channel proteins, aquaporins, and by a subsequent search for vasopressin receptors. Links are shown to the literature and to sequence data for human, rat, and mouse, as well as to relevant web-based resources. Extension of the database is dynamic and is done through a maintenance interface. This permits creation of new categories, updating of existing entries, and addition of new ones. CDDB is a database that organizes lists of genes found in collecting duct tissues from three mammalian species: human, rat, and mouse. Proteins are divided into categories by family relationships and functional classification, and each category is assigned a section in the database. Each section includes links to the literature and to sequence information for genes, proteins, expressed sequence tags, and related information. The user can peruse a section or use a search engine at the bottom of the web page to search the database for a name or abbreviation or for a link to a sequence. Each entry in the database includes links to relevant papers in the kidney and collecting duct literature. It uses links to PubMed to generate MEDLINE searches for retrieval of references. In addition, each entry includes links to curated sequence data available in LocusLink. Individual links are made to sequence and protein data for human, rat, and mouse. Links are then added as curated sequences become available for proteins identified in the renal collecting duct and for proteins identified in kidney and similar in function or homologous to proteins identified in the collecting duct. | expressed sequence tag, expression, family, functional, gene, aquaporin, array, cdna, classification, collecting duct, homologous, human, kidney, literature, mammal, mammalian, microarray, mouse, protein, protein localization and targeting databases, rat, receptor, regulatory, relationship, scan, serial analysis, specie, target, tissue, transporter, vasopressin, water channel protein | has parent organization: National Institutes of Health | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21078 | SCR_000759 | Collecting Duct Database | 2026-02-11 10:56:07 | 0 | |||||||
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WHO Collaborating Centre for Drug Statistics Methodology Resource Report Resource Website 10+ mentions |
WHO Collaborating Centre for Drug Statistics Methodology (RRID:SCR_000677) | data or information resource, database | The official compendium for the Anatomical Therapeutic Chemical Classification System (ATC)-code descriptions. The Centre's main tasks are development and maintenance of the ATC/DDD system, including: * To classify drugs according to the ATC system. * Priority will be given to the classification of single substances, while combination products available internationally (i.e. important fixed combinations) will be dealt with as far as possible. * To establish DDDs for drugs which have been assigned an ATC code. * To review and revise as necessary the ATC classification system and DDDs. * To stimulate and influence the practical use of the ATC system by co-operating with researchers in the drug utilization field. Support: The WHO Collaborating Centre for Drug Statistics Methodology was established in 1982. The Centre is situated in Oslo at the Norwegian Institute of Public Health. The Centre is funded by the Norwegian government. | drug, clinical, human, people, FASEB list | nif-0000-10553 | SCR_000677 | WHOCC | 2026-02-11 10:56:05 | 39 | ||||||||||
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National Science Foundation Graduate Research Fellowship Program Resource Report Resource Website 100+ mentions |
National Science Foundation Graduate Research Fellowship Program (RRID:SCR_001487) | funding resource, graduate program resource | The National Science Foundation's Graduate Research Fellowship Program (GRFP) helps ensure the vitality of the human resource base of science and engineering in the United States and reinforces its diversity. The program recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based master's and doctoral degrees in the U.S. and abroad. The NSF welcomes applications from all qualified students and strongly encourages under-represented populations, including women, under-represented racial and ethnic minorities, and persons with disabilities, to apply for this fellowship. Fellows share in the prestige and opportunities that become available when they are selected. Fellows benefit from a three-year annual stipend of $30,000 along with a $10,500 cost of education allowance for tuition and fees, a one-time $1,000 international travel allowance and the freedom to conduct their own research at any accredited U.S., or foreign institution of graduate education they choose. NSF Fellows are anticipated to become knowledge experts who can contribute significantly to research, teaching, and innovations in science and engineering. So that the nation can build fully upon the strength and creativity of a diverse society, the Foundation welcomes applications from all qualified individuals. Women, under-represented minorites and people with disabilities are encouraged to apply. Those with disabilities are additionally accommodated by the Foundation to provide for the most successful graduate experience possible. Sponsors: This program is supported by the National Science Foundation (NSF). | engineering, fellowship, graduate, human, mathematics, research, science, technology | Free, Freely available | nif-0000-10366 | SCR_001487 | NSF GRFP | 2026-02-11 10:56:14 | 155 | |||||||||
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Human Proteomics Initiative Resource Report Resource Website |
Human Proteomics Initiative (RRID:SCR_002373) | HPI | data or information resource, database | 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. | function, gene, alignment, biologist, clustering, coding, development, genome, human, location, mammalian, modification, ortholog, population, post-translational, protein, proteome, proteomic, proteomics, sequence, splice, structure, subcellular, variant, variation, gold standard |
is related to: UniProt Chordata protein annotation program has parent organization: SIB Swiss Institute of Bioinformatics |
PMID:11301130 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21199 | SCR_002373 | Human Proteome Initiative, UniProtKB/Swiss-Prot Human Proteome Initiative | 2026-02-11 10:56:31 | 0 | ||||||
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AceView Resource Report Resource Website 100+ mentions |
AceView (RRID:SCR_002277) | AceView/WormGenes | data or information resource, database | 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. | est, exon, expression, function, gene, alignment, arabidopsis, cdna, co-alignment, coding, disease, genome, genomic, human, intron, localization, mammal, mouse, mrna, nematode, pathway, phenotype, plant, polyadenylation, promoter, rat, sequence, signal, tissue, transcript, transcriptome, worm, blast, gold standard | has parent organization: NCBI | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21007, r3d100010651 | https://doi.org/10.17616/R3260G | http://www.ncbi.nih.gov/IEB/Research/Acembly/ | SCR_002277 | AceView genes, AceView/WormGenes, The AceView Genes | 2026-02-11 10:56:29 | 186 | |||||
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Full-Malaria: Malaria Full-Length cDNA Database Resource Report Resource Website 1+ mentions |
Full-Malaria: Malaria Full-Length cDNA Database (RRID:SCR_002348) | data or information resource, database | FULL-malaria is a database for a full-length-enriched cDNA library from the human malaria parasite Plasmodium falciparum. Because of its medical importance, this organism is the first target for genome sequencing of a eukaryotic pathogen; the sequences of two of its 14 chromosomes have already been determined. However, for the full exploitation of this rapidly accumulating information, correct identification of the genes and study of their expression are essential. Using the oligo-capping method, this database has produced a full-length-enriched cDNA library from erythrocytic stage parasites and performed one-pass reading. The database consists of nucleotide sequences of 2490 random clones that include 390 (16%) known malaria genes according to BLASTN analysis of the nr-nt database in GenBank; these represent 98 genes, and the clones for 48 of these genes contain the complete protein-coding sequence (49%). On the other hand, comparisons with the complete chromosome 2 sequence revealed that 35 of 210 predicted genes are expressed, and in addition led to detection of three new gene candidates that were not previously known. In total, 19 of these 38 clones (50%) were full-length. From these observations, it is expected that the database contains approximately 1000 genes, including 500 full-length clones. It should be an invaluable resource for the development of vaccines and novel drugs. Full-malaria has been updated in at least three points. (i) 8934 sequences generated from the addition of new libraries added so that the database collection of 11,424 full-length cDNAs covers 1375 (25%) of the estimated number of the entire 5409 parasite genes. (ii) All of its full-length cDNAs and GenBank EST sequences were mapped to genomic sequences together with publicly available annotated genes and other predictions. This precisely determined the gene structures and positions of the transcriptional start sites, which are indispensable for the identification of the promoter regions. (iii) A total of 4257 cDNA sequences were newly generated from murine malaria parasites, Plasmodium yoelii yoelii. The genome/cDNA sequences were compared at both nucleotide and amino acid levels, with those of P.falciparum, and the sequence alignment for each gene is presented graphically. This part of the database serves as a versatile platform to elucidate the function(s) of malaria genes by a comparative genomic approach. It should also be noted that all of the cDNAs represented in this database are supported by physical cDNA clones, which are publicly and freely available, and should serve as indispensable resources to explore functional analyses of malaria genomes. Sponsors: This database has been constructed and maintained by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science (JSPS). This work was also supported by a Special Coordination Funds for Promoting Science and Technology from the Science and Technology Agency of Japan (STA) and a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports and Culture of Japan. | drug, eukaryotic, expression, function, gene, alignment, amino acid, cdna, chromosome, clone, coding, comparative, genome, genomic, human, malaria, medical, nucleotide, oligo-capping, organism, parasite, pathogen, physical, plasmodium falciparum, promoter, protein, region, sequence, sequencing, unicellular eukaryote genome databases, vaccine | has parent organization: University of Tokyo; Tokyo; Japan | PMID:18987005 PMID:14681428 |
nif-0000-21157 | SCR_002348 | Full-Malaria | 2026-02-11 10:56:27 | 2 | ||||||||
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Phenologs Resource Report Resource Website 1+ mentions |
Phenologs (RRID:SCR_005529) | Phenologs | data or information resource, database | Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided. | gene, phenotype, ortholog, genotype, human, mouse, yeast, worm | has parent organization: University of Texas at Austin; Texas; USA | Texas Advanced Research Program ; Welch Foundation ; Packard Fellowship ; March of Dimes ; Texas Institute for Drug and Diagnostic Development ; NSF ; NIH ; NIGMS |
PMID:20308572 | nlx_144624 | SCR_005529 | phenologs.org, Phenologs - Systematic discovery of non-obvious disease models and candidate genes | 2026-02-11 10:57:06 | 4 | ||||||
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TranspoGene Resource Report Resource Website 1+ mentions |
TranspoGene (RRID:SCR_005634) | data or information resource, database | A publicly available database of Transposed elements (TEs) which are located within protein-coding genes of 7 organisms: human, mouse, chicken, zebrafish, fruilt fly, nematode and sea squirt. Using TranspoGene the user can learn about the many aspects of the effect these TEs have on their hosting genes, such as: exonization events (including alternative splicing-related data), insertion of TEs into introns, exons, and promoters, specific location of the TE over the gene, evolutionary divergence of the TE from its consensus sequence and involvement in diseases. TranspoGene database is quickly searchable through its website, enables many kinds of searches and is available for download. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome. | element, eukaryotic, evolutionary, exon, exonization, family, fruit fly, gene, genome, alternative, chicken, coding, disease, divergence, genomic, hosting, human, human genome databases, intron, location, map, maps, mouse, mrna, nematode, organism, pattern, promoter, protein, sea squirt, sequence, splicing, transcript, transcriptome, transposed, viewers, worm, zebrafish | has parent organization: Tel Aviv University; Ramat Aviv; Israel | nif-0000-03579 | SCR_005634 | TranspoGene | 2026-02-11 10:57:11 | 9 | |||||||||
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DBETH - Database for Bacterial ExoToxins for Humans Resource Report Resource Website 1+ mentions |
DBETH - Database for Bacterial ExoToxins for Humans (RRID:SCR_005908) | DBETH | data or information resource, database | Database of Bacterial ExoToxins for Human is a database of sequences, structures, interaction networks and analytical results for 229 exotoxins, from 26 different human pathogenic bacterial genus. All toxins are classified into 24 different Toxin classes. The aim of DBETH is to provide a comprehensive database for human pathogenic bacterial exotoxins. DBETH also provides a platform to its users to identify potential exotoxin like sequences through Homology based as well as Non-homology based methods. In homology based approach the users can identify potential exotoxin like sequences either running BLASTp against the toxin sequences or by running HMMER against toxin domains identified by DBETH from human pathogenic bacterial exotoxins. In Non-homology based part DBETH uses a machine learning approach to identify potential exotoxins (Toxin Prediction by Support Vector Machine based approach). | sequence, structure, interaction network, human, pathogen, bacterial genus, toxin, bacteria, exotoxin, homology, homolog, structure, sequence, domain, prediction, mechanism, activity, bio.tools |
is listed by: Debian is listed by: bio.tools has parent organization: CSIR - Indian Institute of Chemical Biology; Kolkata; India |
Council of Scientific and Industrial Research; New Delhi; India | PMID:22102573 | nlx_149481, biotools:dbeth | https://bio.tools/dbeth | SCR_005908 | Database for Bacterial ExoToxins for Humans | 2026-02-11 10:57:16 | 2 | |||||
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Kabat Database of Sequences of Proteins of Immunological Interest Resource Report Resource Website 1+ mentions |
Kabat Database of Sequences of Proteins of Immunological Interest (RRID:SCR_006465) | data or information resource, database | The Kabat Database determines the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. The Kabat Database searching and analysis tools package is an ASP.NET web-based portal containing lookup tools, sequence matching tools, alignment tools, length distribution tools, positional correlation tools and much more. The searching and analysis tools are custom made for the aligned data sets contained in both the SQL Server and ASCII text flat file formats. The searching and analysis tools may be run on a single PC workstation or in a distributed environment. The analysis tools are written in ASP.NET and C# and are available in Visual Studio .NET 2003/2005/2008 formats. The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences at that time. Bence Jones proteins, mostly from human, were aligned, using the now-known Kabat numbering system, and a quantitative measure, variability, was calculated for every position. Three peaks, at positions 24-34, 50-56 and 89-97, were identified and proposed to form the complementarity determining regions (CDR) of light chains. Subsequently, antibody heavy chain amino acid sequences were also aligned using a different numbering system, since the locations of their CDRs (31-35B, 50-65 and 95-102) are different from those of the light chains. CDRL1 starts right after the first invariant Cys 23 of light chains, while CDRH1 is eight amino acid residues away from the first invariant Cys 22 of heavy chains. During the past 30 years, the Kabat database has grown to include nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules and other proteins of immunological interest. It has been used extensively by immunologists to derive useful structural and functional information from the primary sequences of these proteins. | functional, align, alignment, amino acid, antibody, antigen, biological, cdr, chain, class i, class ii, combining, complementarity, complex, delineation, heavy, histocompatibility, human, immunological, immunological database, light, macromolecule, mhc, molecule, nucleotide, position, protein, receptor, region, sequence, structural, t cell | has parent organization: Northwestern University; Illinois; USA | nif-0000-21233 | SCR_006465 | Kabat Database | 2026-02-11 10:57:20 | 2 | |||||||||
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YanHuang Project Resource Report Resource Website 50+ mentions |
YanHuang Project (RRID:SCR_006077) | data or information resource, database | This database presents the entire DNA sequence of the first diploid genome sequence of a Han Chinese, a representative of Asian population. The genome, named as YH, represents the start of YanHuang Project, which aims to sequence 100 Chinese individuals in 3 years. It was assembled based on 3.3 billion reads (117.7Gbp raw data) generated by Illumina Genome Analyzer. In total of 102.9Gbp nucleotides were mapped onto the NCBI human reference genome (Build 36) by self-developed software SOAP (Short Oligonucleotide Alignment Program), and 3.07 million SNPs were identified. The personal genome data is illustrated in a MapView, which is powered by GBrowse. A new module was developed to browse large-scale short reads alignment. This module enabled users track detailed divergences between consensus and sequencing reads. In total of 53,643 HGMD recorders were used to screen YH SNPs to retrieve phenotype related information, to superficially explain the donor's genome. Blast service to align query sequences against YH genome consensus was also provided. | genome, genetic, adult, chromosome, clinical, control, genomic, human, normal, FASEB list | has parent organization: BGI; Shenzhen; China | nif-0000-03654 | SCR_006077 | YH1 | 2026-02-11 10:57:16 | 53 | |||||||||
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Biomolecular Object Network Databank Resource Report Resource Website 10+ mentions |
Biomolecular Object Network Databank (RRID:SCR_007433) | data or information resource, database | 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 on August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus. | gene, genes, genome, annotation, binding specificity, biological process, complex, dna, genomes, genomic, human, interaction, interactome, ligand, metabolomic, molecular, molecular complex, molecular function, molecular interaction, mouse, ontoglyphs, ontology terms, pathway, photon, protein, protein-protein interactions, proteomic, rna, sequence, structure, sub-cellular localization, taxonomy, unclassified biological entity | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-00571 | SCR_007433 | BOND | 2026-02-11 10:57:33 | 17 | |||||||||
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1000 Genomes Project and AWS Resource Report Resource Website 5000+ mentions |
1000 Genomes Project and AWS (RRID:SCR_008801) | 1000 Genomes Project and AWS | data or information resource, data set | A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow. | genomic data, genome, cloud computing, cloud, human, gene, genetic variation, research, dna |
is used by: HmtVar has parent organization: Amazon Web Services |
nlx_144340 | SCR_008801 | 1000 Genomes Project and Amazon Web Services, 000 Genomes Project Amazon Web Services, 1000 Genomes Project AWS | 2026-02-11 10:57:55 | 7075 | ||||||||
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Network-based Prediction of Human Tissue-specific Metabolism Resource Report Resource Website 1+ mentions |
Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) | data or information resource, data set | THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways. | molecular neuroanatomy resource, brain, pathway, tissue-specific metabolism, human, network-based prediction, cytoscape 2.5, tissue-specific metabolic behavior, network visualization, high degree nodes, hub nodes, currency metabolites, cellular-compartments, cellular compartment, metabolite, cytoplasm, extracellular, lysosome, mitochondrion, nucleus, endoplasmic, peroxisome, metabolic flux |
is related to: Cytoscape has parent organization: Tel Aviv University; Ramat Aviv; Israel |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-00431 | SCR_007392 | Network-based Prediction of Human Tissue-specific Metabolism | 2026-02-11 10:57:34 | 1 |
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