Searching the RRID Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
aGEM Resource Report Resource Website 10+ mentions |
aGEM (RRID:SCR_013349) | aGEM | data or information resource, database | Database platform of an integrated view of eight databases (mouse gene expression resources: EMAGE, GXD, GENSAT, BioGPS, ABA, EUREXPRESS; human gene expression databases: HUDSEN, BioGPS and Human Protein Atlas) that allows the experimentalist to retrieve relevant statistical information relating gene expression, anatomical structure (space) and developmental stage (time). Moreover, general biological information from databases such as KEGG, OMIM and MTB is integrated too. It can be queried using gene and anatomical structure. Output information is presented in a friendly format, allowing the user to display expression maps and correlation matrices for a gene or structure during development. An in-depth study of a specific developmental stage is also possible using heatmaps that relate gene expression with anatomical components. This is a powerful tool in the gene expression field that makes easy the access to information related to the anatomical pattern of gene expression in human and mouse, so that it can complement many functional genomics studies. The platform allows the integration of gene expression data with spatial-temporal anatomic data by means of an intuitive and user friendly display., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. | gene, anatomy, gene expression, anatomical structure, developmental stage, functional genomics, genomics |
is related to: EMAGE Gene Expression Database is related to: Gene Expression Database is related to: Gene Expression Nervous System Atlas is related to: BioGPS: The Gene Portal Hub is related to: Allen Mouse Brain Reference Atlas is related to: Eurexpress is related to: HUDSEN is related to: The Human Protein Atlas is related to: OMIM is related to: KEGG has parent organization: Autonomous University of Madrid; Madrid; Spain |
National Institute for Bioinformatics ; AMIT Programme CDTI CEN-20101014; RESOLVE UE CE:FP7-202047; Ministerio de Ciencia e Innovacion BIO2010-16566; Biostruct-X FP7-Infrastructures-2011-1; Centrosoma 3D CSD2006-00023 |
PMID:22106336 | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_152022 | SCR_013349 | anatomic Gene Expression Mapping | 2026-09-03 05:03:43 | 12 | |||||
|
MLTreeMap Resource Report Resource Website 1+ mentions |
MLTreeMap (RRID:SCR_004792) | MLTreeMap | analysis service resource, data analysis service, production service resource, service resource | Data analysis service that analyzes DNA sequences and determines their most likely phylogenetic origin. Its main use is in metagenomics projects, where DNA is isolated directly from natural environments and sequenced (the organisms from which the DNA originates are often entirely undescribed). It will search such sequences for suitable marker genes, and will use maximum likelihood analysis to place them in the ''''Tree of Life''''. This placement is more reliable than simply assessing the closest relative of a sequence using BLAST. More importantly, MLTreeMap decides not only who is the closest relative of your query sequence, but also how deep in the tree of life it probably branched off. Additionally, MLTreeMap searches the sequences for genes, which are coding for key enzymes of important functional pathways, such as RuBisCo, methane monooxygenase or nitrogenase. In case of a positive hit, MLTreeMap uses maximum likelihood analysis to place them in the respective ''''gene-family tree''''. | phylogeny, gene, fasta, dna sequence, nucleotide sequence, metagenomics, metagenome, bio.tools |
is listed by: OMICtools is listed by: Debian is listed by: bio.tools is related to: COG has parent organization: University of Zurich; Zurich; Switzerland |
PMID:20687950 | biotools:mltreemap, OMICS_01457 | https://bio.tools/mltreemap | SCR_004792 | Phylogenetic analysis of metagenomics sequence data | 2026-09-03 05:01:35 | 4 | ||||||
|
CandiSNPer Resource Report Resource Website |
CandiSNPer (RRID:SCR_005173) | CandiSNPer | service resource, software resource, source code | A webtool which helps in characterizing Single Nucleotide Polymorphisms (SNPs) that are located in the vicinity of an SNP of interest (start SNP). Along with the computation of the maximal Linkage Disequilibrium (LD) region around the start SNP. CandiSNPer provides additional information with respect to the molecular consequences of the SNPs and the genes located in the LD region. | single nucleotide polymorphism, gene, plot, linkage disequilibrium, variant, genome-wide association study, genotyping, perl, r |
is listed by: OMICtools is related to: Ensembl has parent organization: Humboldt University of Berlin; Berlin; Germany |
PMID:20172942 | Free for academic use | OMICS_00169 | SCR_005173 | 2026-09-03 05:01:48 | 0 | |||||||
|
AtProbe Resource Report Resource Website |
AtProbe (RRID:SCR_005412) | AtProbe | data or information resource, database | Arabidopsis thaliana promoter binding element database that focuses on specific binding elements on known genes, found with experimental methods. | gene, binding element |
is listed by: OMICtools has parent organization: Cold Spring Harbor Laboratory |
Free | OMICS_00550 | SCR_005412 | AtProbe: Arabidopsis thaliana Promoter Binding Element Database, Arabidopsis thaliana Promoter Binding Element Database | 2026-09-03 05:02:02 | 0 | |||||||
|
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 | 2026-09-03 05:01:50 | 4 | ||||||
|
International Knockout Mouse Consortium Resource Report Resource Website 50+ mentions |
International Knockout Mouse Consortium (RRID:SCR_005574) | IKMC | data or information resource, database | Database of the international consortium working together to mutate all protein-coding genes in the mouse using a combination of gene trapping and gene targeting in C57BL/6 mouse embryonic stem (ES) cells. Detailed information on targeted genes is available. The IKMC includes the following programs: * Knockout Mouse Project (KOMP) (USA) ** CSD, a collaborative team at the Children''''s Hospital Oakland Research Institute (CHORI), the Wellcome Trust Sanger Institute and the University of California at Davis School of Veterinary Medicine , led by Pieter deJong, Ph.D., CHORI, along with K. C. Kent Lloyd, D.V.M., Ph.D., UC Davis; and Allan Bradley, Ph.D. FRS, and William Skarnes, Ph.D., at the Wellcome Trust Sanger Institute. ** Regeneron, a team at the VelociGene division of Regeneron Pharmaceuticals, Inc., led by David Valenzuela, Ph.D. and George D. Yancopoulos, M.D., Ph.D. * European Conditional Mouse Mutagenesis Program (EUCOMM) (Europe) * North American Conditional Mouse Mutagenesis Project (NorCOMM) (Canada) * Texas A&M Institute for Genomic Medicine (TIGM) (USA) Products (vectors, mice, ES cell lines) may be ordered from the above programs. | gene, knock out mouse, chromosome, allele, c57bl/6, embryonic stem cell, vector, mutant, es cell, genome, targeting, gene list, FASEB list |
is related to: Texas A and M Institute for Genomic Medicine is related to: European Mouse Mutant Archive is related to: CMMR - Canadian Mouse Mutant Repository is parent organization of: EUCOMMTOOLS is parent organization of: North American Conditional Mouse Mutagenesis Project is parent organization of: European Conditional Mouse Mutagenesis Program is parent organization of: Knockout Mouse Project |
European Union ; NHGRI HG004074 |
PMID:22968824 PMID:21677750 |
nlx_146200 | SCR_005574 | 2026-09-03 05:01:51 | 68 | |||||||
|
PolySearch Resource Report Resource Website 10+ mentions |
PolySearch (RRID:SCR_005291) | PolySearch | analysis service resource, data analysis service, production service resource, service resource | A web-based tool that supports more than 50 different classes of queries against nearly a dozen different types of text, scientific abstract or bioinformatic databases. The typical query supported by PolySearch is Given X, find all Y''s where X or Y can be diseases, tissues, cell compartments, gene/protein names, SNPs, mutations, drugs and metabolites. PolySearch also exploits a variety of techniques in text mining and information retrieval to identify, highlight and rank informative abstracts, paragraphs or sentences. | text mining, disease, gene, protein, drug, metabolite, snp, gene sequence, pathway, tissue, gene family, subcellular localization, organ |
is listed by: OMICtools has parent organization: University of Alberta; Alberta; Canada |
OMICS_01194 | SCR_005291 | 2026-09-03 05:01:44 | 20 | |||||||||
|
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 | 2026-09-03 05:01:52 | 9 | |||||||||
|
TRANSFAC Resource Report Resource Website 100+ mentions |
TRANSFAC (RRID:SCR_005620) | TRANSFAC | data or information resource, database | Manually curated database of eukaryotic transcription factors, their genomic binding sites and DNA binding profiles. Used to predict potential transcription factor binding sites. | Curated, eucaryotic, transcription, factor, genomic, binding, site, sequence, regulated, gene, bio.tools |
is listed by: OMICtools is listed by: Debian is listed by: bio.tools is listed by: Gene Regulation Databases is related to: TRANSPATH is related to: Babelomics is related to: GeneTrail works with: rVista |
European Commission ; German Ministry of Education and Research |
PMID:12520026 | Free, Freely available | biotools:transfac, nif-0000-03576 | http://www.biobase-international.com/pages/index.php?id=transfac, http://gene-regulation.com/pub/databases.html, https://bio.tools/transfac | SCR_005620 | 2026-09-03 05:01:52 | 266 | |||||
|
FuncExpression Resource Report Resource Website |
FuncExpression (RRID:SCR_005773) | FuncExpression | analysis service resource, data analysis service, production service resource, service resource | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 11, 2012. FuncExpression is a web-based resource for functional interpretation of large scale genomics data. FuncExpression can be used for the functional comparison of plant, animal, and fungal gene name lists generated from genomics and proteomics experiments. Multiple gene lists can be classified, compared and visualized. FuncExpression supports two way-integration of plant gene functional information and the gene expression data, which allows for further cross-validation with plant microarray data from related experiments at BarleyBase. Platform: Online tool | statistical analysis, genomics, compare, function, plant, animal, fungus, gene, proteomics, gene expression, microarray |
is listed by: Gene Ontology Tools is related to: Gene Ontology is related to: PLEXdb - Plant Expression Database has parent organization: Iowa State University; Iowa; USA |
THIS RESOURCE IS NO LONGER IN SERVICE | nlx_149237 | SCR_005773 | 2026-09-03 05:02:02 | 0 | ||||||||
|
Literature-derived human gene-disease network Resource Report Resource Website 1+ mentions |
Literature-derived human gene-disease network (RRID:SCR_005653) | LHGDN | data or information resource, database | A text mining derived database with focus on extracting and classifying gene-disease associations with respect to several biomolecular conditions. It uses a machine learning based algorithm to extract semantic gene-disease relations from a textual source of interest. The semantic gene-disease relations were extracted with F-measures of 78. More specifically, the textual source utilized here originates from Entrez Gene''''s GeneRIF (Gene Reference Into Function) database (Mitchell, et al., 2003). LHGDN was created based on a GeneRIF version from March 31st, 2009, consisting of 414241 phrases. These phrases were further restricted to the organism Homo sapiens, which resulted in a total of 178004 phrases. We benchmark our approach on two different tasks. The first task is the identification of semantic relations between diseases and treatments. The available data set consists of manually annotated PubMed abstracts. The second task is the identification of relations between genes and diseases from a set of concise phrases, so-called GeneRIF (Gene Reference Into Function) phrases. In our experimental setting, we do not assume that the entities are given, as is often the case in previous relation extraction work. Rather the extraction of the entities is solved as a subproblem. Compared with other state-of-the-art approaches, we achieve very competitive results on both data sets. To demonstrate the scalability of our solution, we apply our approach to the complete human GeneRIF database. The resulting gene-disease network contains 34758 semantic associations between 4939 genes and 1745 diseases. The gene-disease network is publicly available as a machine-readable RDF graph. We extend the framework of Conditional Random Fields towards the annotation of semantic relations from text and apply it to the biomedical domain. Our approach is based on a rich set of textual features and achieves a performance that is competitive to leading approaches. The model is quite general and can be extended to handle arbitrary biological entities and relation types. The resulting gene-disease network shows that the GeneRIF database provides a rich knowledge source for text mining. | gene, disease, gene-disease association, text-mining, conditional random field, entity recognition |
is used by: DisGeNET is related to: linked life data - a semantic data integration platform for the biomedical domain has parent organization: Ludwig-Maximilians-University; Munich; Germany |
German Federal Ministry of Economics and Technology ; THESEuropean UnionS project |
PMID:18433469 | Available under Creative Commons Attribution v3 Unported; please cite. | nlx_151713 | SCR_005653 | 2026-09-03 05:01:52 | 1 | ||||||
|
BiGG Database Resource Report Resource Website 100+ mentions |
BiGG Database (RRID:SCR_005809) | BiGG | data or information resource, database | A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. | biochemical, genetics, genomics, genome, metabolic network, reconstruction, model, metabolic pathway, gene, protein, reaction, metabolite, metabolic reconstruction, compound, pathway, FASEB list |
uses: SBML is used by: BiGGR is listed by: 3DVC has parent organization: University of California at San Diego; California; USA |
NIH ; Ruth L. Kirschstein National Research Service Award - NIH Bioinformatics Training ; University of California at San Diego; California; USA ; Calit2 summer research scholarship ; NIGMS GM00806-06 |
PMID:20426874 | nlx_149299, r3d100011567 | https://doi.org/10.17616/R3MG9M | SCR_005809 | BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions, BiGG - a Biochemical Genetic and Genomic knowledgebase | 2026-09-03 05:02:03 | 145 | |||||
|
ProfCom - Profiling of complex functionality Resource Report Resource Website 1+ mentions |
ProfCom - Profiling of complex functionality (RRID:SCR_005797) | ProfCom | analysis service resource, data analysis service, production service resource, service resource | Profiling of Complex Functionality (ProfCom) is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of complex function. A complex function is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes. Platform: Online tool | gene, function, profile, gene ontology, complex function, statistical analysis, bio.tools |
is listed by: Gene Ontology Tools is listed by: bio.tools is listed by: Debian is related to: Gene Ontology has parent organization: Institute of Bioinformatics and Systems Biology; Neuherberg; Germany |
DFG | PMID:16959266 | Free for academic use | biotools:profcom, nlx_149276 | https://bio.tools/profcom | SCR_005797 | Profiling of Complex Functionality, Profiling of Complex Functionality (ProfCom) | 2026-09-03 05:02:08 | 4 | ||||
|
Computational Biology at ORNL Resource Report Resource Website |
Computational Biology at ORNL (RRID:SCR_005710) | Computational Biology at ORNL | analysis service resource, data analysis service, production service resource, service resource | We are the Computational Biology and Bioinformatics Group of the Biosciences Division of Oak Ridge National Laboratory. We conduct genetics research and system development in genomic sequencing, computational genome analysis, and computational protein structure analysis. We provide bioinformatics and analytic services and resources to collaborators, predict prospective gene and protein models for analysis, provide user services for the general community, including computer-annotated genomes in Genome Channel. Our collaborators include the Joint Genome Institute, ORNL''s Computer Science and Mathematics Division, the Tennessee Mouse Genome Consortium, the Joint Institute for Biological Sciences, and ORNL''s Genome Science and Technology Graduate Program. | genetics, research, system development, genomic sequencing, computation, genome analysis, protein structure, analysis, gene, protein, gene annotation, annotation, genome | has parent organization: Oak Ridge National Laboratory | nlx_149161 | SCR_005710 | Computational Biology at Oak Ridge National Laboratory, Computational Biology and Bioinformatics Group at ORNL, Computational Biology Bioinformatics Group at ORNL | 2026-09-03 05:01:54 | 0 | ||||||||
|
GOtcha Resource Report Resource Website 1+ mentions |
GOtcha (RRID:SCR_005790) | GOtcha | analysis service resource, data analysis service, production service resource, service resource | GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool | function, protein, prediction, genome, annotation, gene, statistical analysis |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: University of Dundee; Scotland; United Kingdom |
Wellcome Trust 060269; European Union fifth framework QLRI-CT-2000-00127 |
PMID:15550167 | Free for academic use | nlx_149269 | http://www.compbio.dundee.ac.uk/Software/GOtcha/gotcha.html | SCR_005790 | 2026-09-03 05:02:01 | 3 | |||||
|
FaceBase Biorepository Resource Report Resource Website 1+ mentions |
FaceBase Biorepository (RRID:SCR_006001) | FaceBase Biorepository | biomaterial supply resource, material resource, tissue bank | THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. FaceBase Biorepository is now collecting biological samples from people with cleft lip/palate and their family members. Information for Prospective Cases: Clefts of the lip and/or palate can be caused by a wide range of genetic, environmental and other factors. The FaceBase Biorepository will serve as a common source of both biological samples and information that can be made available to investigators trying to determine the underlying cause of these common birth defects. Genetic studies, in particular, will benefit from both family history information and having samples from affected individuals as well as their family members. DNA is the information containing molecules found in all the cells of our body and can be easily obtained from material such as blood or saliva samples. As part of the FaceBase Biorepository, we are requesting families to submit biological samples from specific family members as well as information from other family members that might be affected with either the same condition or a similar condition. The medical and family history information that is collected includes other relevant information such as exposure to possible environmental causes during pregnancy. The biorepository is managed by Nichole Nidey, a research study coordinator, and Jeff Murray, a pediatric clinical geneticist and researcher. They are available to speak with family members regarding questions they may have, including providing information about the biorepository and making arrangements for the collection of samples for those who wish to participate. All participation is voluntary. Your name or other personally identifiable information (name, address, etc) will be removed before information is placed in the biorepository. Summary data to show how the database itself has been used overall as well as updates on whether specific findings might have been made using this database will be available on the FaceBase website at www.facebase.org. A newsletter containing this information will also be given to families and referring clinicians so that they may discuss the specifics with the families if there appears to be information that might be relevant in a particular case. Families will also need to sign a consent form that has been approved by the Institutional Review Board at the University of Iowa. Also, any submitted samples or data can also be removed from the database at any time should the family no longer wish to participate. Investigators interested in requesting DNA samples or for more information, please contact cleftresearch (at) uiowa.edu, Nichole Nidey, nichole-nidey (at) uiowa.edu or (319) 353-4365, or Jeff Murray, jeff-murray (at) uiowa.edu. | birth defect, genetic, environment, gene |
is listed by: One Mind Biospecimen Bank Listing has parent organization: FaceBase |
Cleft lip, Cleft palate, Family member, Campomelic Dysplasia, Chromosome Abnormality, Congenital Heart Disease, Facial clefting-Tessier Type 4, Gordon Syndrome, Hemifacial Microsomia, Idiopathic Short Stature, Marshall/Stickler, Microtia, Multiple Congenital Anomaly, Neurofibromatosis, Pierre Robin, Popliteal Pterygium Syndrome, Robinow, Downs syndrome, Townes-Brock Syndrome, Van der Woude Syndrome, Popliteal Pterygium Syndrome, Wildervanck Syndrome | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_151379 | SCR_006001 | 2026-09-03 05:02:05 | 1 | |||||||
|
GOSlimViewer Resource Report Resource Website 10+ mentions |
GOSlimViewer (RRID:SCR_005665) | GOSlimViewer | analysis service resource, data analysis service, production service resource, service resource | Service to summarize the GO function associated with a data set using prepared GO Slim sets. The input is a tab separated list of gene product IDs and GO IDs. | agriculture, browser, slimmer-type tool, gene ontology, gene, ontology, ontology or annotation browser |
is listed by: Gene Ontology Tools is listed by: OMICtools is related to: Gene Ontology has parent organization: AgBase |
USDA ; Mississippi State University; Mississippi; USA ; MSU Office of Research ; MSU Bagley College of Engineering ; MSU College of College of Veterinary Medicine ; MSU Life Science and Biotechnology Institute |
PMID:17135208 PMID:16961921 |
Free for academic use | nlx_149103, OMICS_02270 | SCR_005665 | GO Slim Viewer, GOSlim Viewer | 2026-09-03 05:01:58 | 40 | |||||
|
Expression Profiler Resource Report Resource Website 1+ mentions |
Expression Profiler (RRID:SCR_005821) | Expression Profiler | analysis service resource, data analysis service, production service resource, service resource | THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice. | other analysis, cluster, analysis, visualization, gene expression, genomic, gene ontology, gene association, microarray, protein-protein interaction, gene, bio.tools |
is listed by: Gene Ontology Tools is listed by: Debian is listed by: bio.tools is related to: Gene Ontology has parent organization: European Bioinformatics Institute |
European Union ; Wellcome Trust ; Estonian Science Foundation 5724; Estonian Science Foundation 5722 |
PMID:15215431 | THIS RESOURCE IS NO LONGER IN SERVICE | biotools:expression_profiler, nlx_149323 | https://bio.tools/expression_profiler | SCR_005821 | Expression Profiler at the EBI | 2026-09-03 05:02:02 | 6 | ||||
|
SGD Gene Ontology Slim Mapper Resource Report Resource Website 10+ mentions |
SGD Gene Ontology Slim Mapper (RRID:SCR_005784) | GO Slim Mapper | analysis service resource, data analysis service, production service resource, service resource | The GO Slim Mapper (aka GO Term Mapper) maps the specific, granular GO terms used to annotate a list of budding yeast gene products to corresponding more general parent GO slim terms. Uses the SGD GO Slim sets. Three GO Slim sets are available at SGD: * Macromolecular complex terms: protein complex terms from the Cellular Component ontology * Yeast GO-Slim: GO terms that represent the major Biological Processes, Molecular Functions, and Cellular Components in S. cerevisiae * Generic GO-Slim: broad, high level GO terms from the Biological Process and Cellular Component ontologies selected and maintained by the Gene Ontology Consortium (GOC) Platform: Online tool | gene, annotation, gene ontology, protein complex, biological process, molecular function, cellular component, gene ontology, orf, yeast, statistical analysis, slimmer-type tool, function |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: SGD |
Free for academic use | nlx_149258 | SCR_005784 | GO Term Mapper, Gene Ontology Slim Mapper | 2026-09-03 05:02:03 | 31 | |||||||
|
omniBiomarker Resource Report Resource Website 1+ mentions |
omniBiomarker (RRID:SCR_005750) | omniBiomarker | analysis service resource, data analysis service, production service resource, service resource | omniBiomarker is a web-application for analysis of high-throughput -omic data. Its primary function is to identify differentially expressed biomarkers that may be used for diagnostic or prognostic clinical prediction. Currently, omniBiomarker allows users to analyze their data with many different ranking methods simultaneously using a high-performance compute cluster. The next release of omniBiomarker will automatically select the most biologically relevant ranking method based on user input regarding prior knowledge. The omniBiomarker workflow * Data: Gene Expression * Algorithms: Knowledge-Driven Gene Ranking * Differentially expressed Genes * Clinical / Biological Validation * Knowledge: NCI Thesaurus of Cancer, Cancer Gene Index * back to Algorithms | gene, gene expression, algorithm, cancer, cancer gene, cancer gene index, biocomputing, biomarker, clinical, gene ranking |
has parent organization: Georgia Institute of Technology; Georgia; USA has parent organization: Emory University; Georgia; USA |
Cancer | Georgia Cancer Coalition ; NCI U54CA119338; NCI R01CA108468 |
PMID:19695674 | nlx_149210 | SCR_005750 | omniBiomarker: Knowledge-Driven Biomarker Identification and Data Combination | 2026-09-03 05:02:08 | 3 |
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the NIF Resources search. From here you can search through a compilation of resources used by NIF and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that NIF has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on NIF then you can log in from here to get additional features in NIF such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
If you are logged into NIF you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter the data by.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
