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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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QuasiSeq Resource Report Resource Website 10+ mentions |
QuasiSeq (RRID:SCR_001715) | QuasiSeq | software resource | Software package to apply the QL, QLShrink and QLSpline methods to quasi-Poisson or quasi-negative binomial models for identifying differentially expressed genes in RNA-seq data. | differential expression, gene, rna-seq, next generation sequencing, gene expression, mrna | is listed by: OMICtools | PMID:23104842 | Free, Available for download, Freely available | OMICS_01963 | http://cran.r-project.org/web/packages/QuasiSeq/index.html | SCR_001715 | 2026-09-05 06:24:38 | 20 | ||||||
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Kidney and Urinary Pathway Knowledge Base Resource Report Resource Website 1+ mentions |
Kidney and Urinary Pathway Knowledge Base (RRID:SCR_001746) | KUPKB | analysis service resource, data analysis service, data or information resource, data repository, data set, production service resource, service resource, storage service resource | A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made. | kidney, urinary, urine, pathway, molecule, visualizer, gene, protein, mirna, metabolite, mrna, microarray, ortholog, rdf, renal cell, anatomy, animal model, disease, sparql, proteomics, ontology, biomarker, gene expression, physiology, pathology |
is related to: NIDDK Information Network (dkNET) is related to: Gene Expression Omnibus is related to: Gene Ontology is related to: KEGG has parent organization: University of Manchester; Manchester; United Kingdom has parent organization: National Institute of Health and Medical Research; Rennes; France |
Kidney disease | European Union ; FP7 ; ICT-2007.4.4 e-LICO project |
PMID:21624162 | THIS RESOURCE IS NO LONGER IN SERVICE. | nlx_154134 | http://www.e-lico.eu/kupkb | SCR_001746 | Kidney & Urinary Pathway Knowledge Base | 2026-09-05 06:24:38 | 2 | |||
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Generic Model Organism Database Project Resource Report Resource Website 1+ mentions |
Generic Model Organism Database Project (RRID:SCR_001731) | GMOD | data or information resource, database, portal, software resource, topical portal | A collection of open source software tools for creating and managing genome-scale biological databases. GMOD is made up databases, applications, and adaptor software that connects these components together. You can use it to create a small laboratory database of genome annotations, or a large web-accessible community database. At first GMOD just featured model organisms but now any organism with any kind of sequence associated with it is a good candidate as a subject for a GMOD database. There are GMOD databases with just protein sequence in them, with EST sequence only, those that are concerned primarily with gene expression, and even those dedicated to collections of RNA sequence. They have also heard of GMOD databases for oligonucleotides and plasmids. | genome, biological database, model organism, software, annotation, gene, sequence, expressed sequence tag, gene expression, rna sequence, oligonucleotide, plasmid |
is related to: Generic GO Term Mapper is related to: Generic GO Term Finder has parent organization: USDA Agricultural Research Service has parent organization: National Human Genome Research Institute has parent organization: National Institute of General Medical Sciences is parent organization of: SynView is parent organization of: Apollo is parent organization of: GBrowse is parent organization of: CMAP is parent organization of: GBrowse syn |
Free, Freely Available | nif-0000-10234 | SCR_001731 | Generic Model Organism Database | 2026-09-05 06:24:38 | 7 | |||||||
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Cerebellar Gene Regulation in Time and Space Database Resource Report Resource Website 1+ mentions |
Cerebellar Gene Regulation in Time and Space Database (RRID:SCR_001699) | Cb GRiTS | data or information resource, data set, database | THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Time-series data sets spanning twelve time-points between E12-P9 for exploring cerebellar development of the mouse in time and space. The database contains a number of mutant / wildtype microarray datasets including two complete wildtype microarray time-series (C57BL/6 and DBA/2J). The dataset also includes in situ hybridization and bioinformatic analyses. Exploration of this dataset will allow the investigator to assess differential gene expression profiles from a developing mutant cerebella, to assess the temporal changes in gene expression in the wildtype, and to verify the cellular expression of these genes in images from our in situ hybridization library. Using the database, the investigator can explore the developmental expression or differential expression patterns of a particular gene, or create lists of similarly expression genes by building simple search algorithms. These lists can then be mined across all the datasets in both space and time. Cb GRiTS's current datasets represent gene expression analyses from multiple cerebellar mutant and wildtype single time-point and developmental series. | anova, helmert analysis, polynomial analysis, differential equation modeling, paraclique analysis, parent/child analysis, microarray, mouse, mouse model, c57bl/6, dba/2j, in situ hybridization, bioinformatic analyses, gene expression, developmental expression, differential expression, development, cerebellum, phenotype, paraclique analysis, dynamic system modeling, prenatal, adult mouse, embryonic mouse, time series, gene | has parent organization: University of British Columbia; British Columbia; Canada | NICHD HD052472 | PMID:25446528 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-10192 | http://grits.dglab.org/ | SCR_001699 | Cb GRiTS Database | 2026-09-05 06:24:38 | 1 | ||||
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International Union of Physiological Sciences: Physiome Project Resource Report Resource Website 1+ mentions |
International Union of Physiological Sciences: Physiome Project (RRID:SCR_001760) | data or information resource, portal, topical portal | The Physiome Project is a worldwide public domain effort to provide a computational framework for understanding human and other eukaryotic physiology. It aims to develop integrative models at all levels of biological organization, from genes to the whole organism via gene regulatory networks, protein pathways, integrative cell function, and tissue and whole organ structure/function relations. Additionally, an important goal of the project is to develop applications for teaching physiology. Current projects include the development of: - ontologies to organize biological knowledge and access to databases - markup languages to encode models of biological structure and function in a standard format for sharing between different application programs and for re-use as components of more comprehensive models - databases of structure at the cell, tissue and organ levels - software to render computational models of cell function such as ion channel electrophysiology, cell signaling and metabolic pathways, transport, motility, the cell cycle, etc. in 2 & 3D graphical form - software for displaying and interacting with the organ models which will allow the user to move across all spatial scales Sponsors: This project is supported by the International Union of Physiological Sciences (IUPS), the IEEE Engineering. in Medicine and Biology (EMBS), and the International Federation for Medical and Biological Engineering (IFMBE) | electrophysiology, eukaryotic, framework, function, gene, 3d form, biological, cell, cell cycle, channel, computational, human, ion, metabolic, model, motility, network, organ, organism, pathway, physiology, physiome, protein, public domain, regulatory, signaling, software, structure, tissue, transport | is related to: Physiome Model Repository | Free, Freely available | nif-0000-10266 | http://www.physiome.org.nz/ | SCR_001760 | IUPS Physiome | 2026-09-05 06:24:38 | 2 | |||||||
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International Neuroinformatics Coordinating Facility: Blue Gene/L Access Resource Report Resource Website |
International Neuroinformatics Coordinating Facility: Blue Gene/L Access (RRID:SCR_001755) | data computation service | Through this site, INCF provides he neuroinformatics community with access to an IBM Blue Gene/L supercomputer. INCF owns a share of a BlueGene/L (BG/L) supercomputer located at the Parallel Computer Center (PDC) at The Royal Institute of Technology (KTH) in Stockholm. Allocations are now available through the INCF Secretariat. During an initial evaluation phase, a limited numbers of large-scale computing projects will be selected, based on the suitability of the project for supercomputing. Research groups with limited access to supercomputers at their home institutions are given priority. Approved projects are regularly re-evaluated. New projects are approved based on availability and usage load of the BG/L. The Blue Gene/L supercomputer project is aimed at expanding the horizon of high-performance computing to unprecedented levels of scale and performance. Blue Gene/L is the first supercomputer in the Blue Gene family. The full Blue Gene/L consists of 64 racks containing 65,536 high-performance compute nodes. Each node (nodes and chips are the same in the Blue Gene system) contains two embedded 32-bit PowerPC processors. Furthermore, the same chip that is used for compute nodes is also used for the 1,024 I/O nodes. A three-dimensional torus network and a collective network are used to interconnect all nodes. The full system contains 33 terabytes of main memory; it is designed to achieve 183.5 teraflops peak performance using one of the processors of each node for computation and the other processor for communication, and 367 teraflops using both processors for computation. Another key architectural feature of this supercomputer is the link chip component and five Blue Gene/L networks, the PowerPC 440 core and floating-point enhancements, the on-chip and off-chip distributed memory system, the node- and system-level design for high reliability, and the comprehensive approach to fault isolation. One of the key objectives in Blue Gene/L design is to achieve cost/performance comparable to the COTS (Commodity Off The Shelf) approach, while at the same time incorporating a processor and network combination so powerful that it revolutionizes the performance of supercomputer systems. Sponsors: This resource is supported by the INCF. | gene, chip, computation, computing project, memory, neuroinformatics, node, parallel computer, processor, supercomputer | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-10263 | SCR_001755 | INCF Blue Gene/L Access | 2026-09-05 06:24:38 | 0 | |||||||||
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MACH 1.0 Resource Report Resource Website 50+ mentions |
MACH 1.0 (RRID:SCR_001759) | data analysis software, data processing software, software application, software resource | A Markov Chain based software tool for haplotyping, genotype imputation and disease association analysis that can resolve long haplotypes or infer missing genotypes in samples of unrelated individuals. | gene, genetic, genomic, haplotype, genotype, genomic analysis, imaging genomics, imputation, snp, gene, haplotyping, sequence |
is listed by: OMICtools is listed by: Genetic Analysis Software is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is related to: Mach2dat has parent organization: University of Michigan; Ann Arbor; USA |
PMID:21058334 PMID:19715440 |
Free | nlx_154202, OMICS_00064 | SCR_001759 | MArkov Chain Haplotyper MINIMAC, MArkov Chain Haplotyping | 2026-09-05 06:24:38 | 58 | |||||||
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Homology Maps Page Resource Report Resource Website 1+ mentions |
Homology Maps Page (RRID:SCR_001666) | data or information resource, portal, topical portal | This page provides quick access to the Comparative mapping functions available in the Map Viewer. Currently, comparative maps are calculated using HomoloGene orthology predictions. Once the gene pairs have been established, blocks of conserved syteny can be established using the positions of each gene object in their respective builds. Sponsors: This resource is supported by NCBI. | function, gene, comparative, homology, map, mapping, orthology, protein | has parent organization: NCBI | Free, Freely Available | nif-0000-25559 | SCR_001666 | Homology | 2026-09-05 06:24:37 | 2 | ||||||||
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Chilibot: Gene and Protein relationships from MEDLINE Resource Report Resource Website 10+ mentions |
Chilibot: Gene and Protein relationships from MEDLINE (RRID:SCR_001705) | Chilibot | analysis service resource, data analysis service, data or information resource, database, production service resource, service resource | Data analysis service that searches PubMed literature database (abstracts) about specific relationships between proteins, genes, or keywords using a NLP-based text-mining approach. The results are returned as a graph. The synonym database used in Chilibot is available, without fee, for academic use only. Several different search methods are supported including: * searching for relationship between two genes, proteins or keywords * searching for relationships between many genes, proteins, or keywords * searching for relationships between two lists of genes, proteins, or keywords Advanced options include: * Automated hypothesis generation (graph) * Restricting context using keywords * Providing your own synonyms * Modifying synonyms provided by Chilibot * Color coding nodes with gene expression values * Special search: modulation | drug, gene, literature, natural language processing, protein, text-mining, network, keyword, biological concept, graph, bio.tools |
is listed by: OMICtools is listed by: 3DVC is listed by: bio.tools is listed by: Debian is related to: PubMed has parent organization: University of Tennessee Health Science Center; Tennessee; USA |
PHS DA-03977 | PMID:15473905 | THIS RESOURCE IS NO LONGER IN SERVICE | OMICS_01176, nif-0000-10196, biotools:chilibot | https://bio.tools/chilibot | SCR_001705 | Chilibot - Mining PubMed for relationships | 2026-09-05 06:24:38 | 33 | ||||
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Diabetes Disease Portal Resource Report Resource Website |
Diabetes Disease Portal (RRID:SCR_001660) | Diabetes Disease Portal | data or information resource, data set, disease-related portal, portal, topical portal | An integrated resource for information on genes, QTLs and strains associated with diabetes. The portal provides easy acces to data related to both Type 1 and Type 2 Diabetes and Diabetes-related Obesity and Hypertension, as well as information on Diabetic Complications. View the results for all the included diabetes-related disease states or choose a disease category to get a pull-down list of diseases. A single click on a disease will provide a list of related genes, QTLs, and strains as well as a genome wide view of these via the GViewer tool. A link from GViewer to GBrowse shows the genes and QTLs within their genomic context. Additional pages for Phenotypes, Pathways and Biological Processes provide one-click access to data related to diabetes. Tools, Related Links and Rat Strain Models pages link to additional resources of interest to diabetes researchers. | gene, quantitative trait locus, strain, diabetic complication, genome, gviewer, genomic, phenotype, pathway, biological process, chromosome, visualization, molecular function, cellular component, synteny |
is related to: NIDDK Information Network (dkNET) is related to: Gene Ontology has parent organization: Rat Genome Database (RGD) |
Type 1 diabetes, Type 2 diabetes, Diabetes, Obesity, Hyperlipidemia, Metaboic disease, Hypertension | Free, Freely Available | nlx_153942 | http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=diabetes | SCR_001660 | 2026-09-05 06:24:37 | 0 | ||||||
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Salk Institute for Medical Research: Laboratory for Cognitive Neuroscience Resource Report Resource Website |
Salk Institute for Medical Research: Laboratory for Cognitive Neuroscience (RRID:SCR_001851) | Salk Institute LCN | data or information resource, portal, topical portal | The Salk Institute's Laboratory for Cognitive Neuroscience (LCN) is dedicated to the study of the neural and genetic underpinnings of language and cognition. The LCN organizes its resources into two research foci: Linking Gene, Brain, and Cognition, and Language, Modality and the Brain. Linking Gene, Brain, and Cognition: Behavioral Neurogenetics: - This research is designed to increase the understanding of genetically based disorders, to investigate the consequences of genetic alterations on the development of the brain, and to explore the resulting alteration of cognitive capabilities. Language, Modality, and the Brain: - The focus of this research is to obtain a greater understanding of how language and cognition are represented in the brain. Sponsors: This resource is supported by LCN. | gene, genetically based disorder, genetic alteration, genetics, brain, cognition, cognitive neuroscience, development, modality, neural, language | Free, Freely available | nif-0000-10415 | http://www.lcn.salk.edu/ | SCR_001851 | Salk Institute LCN | 2026-09-05 06:24:40 | 0 | |||||||
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Mining On-Line Expert on MedLine Resource Report Resource Website 1+ mentions |
Mining On-Line Expert on MedLine (RRID:SCR_001848) | analysis service resource, data analysis service, production service resource, service resource, software application, software resource, text-mining software | MedMOLE improves the comprehension of microarray experimental results by grouping co-regulated genes on the basis of the informational content of MEDLINE documents. The tool relies on two components: a gene name extractor and a mining algorithm. The name extractor is based on existing dictionaries of gene names and aliases. The mining algorithm analyses the co-occurrences of words in the selected documents in order to automatically interpret the context, identify where the gene names appear, and map documents/genes into functional classes. DNA microarray technology is a high throughput method for gaining information on gene function. This large amount of data can be analyzed to identify groups of genes that share common expression characteristics, but the obtained results provide little information regarding the presence of functional biological correlations of genes within clusters. The published literature, on the other hand, provides a potential source of information to assist in interpretation of clustering results. We have developed a tool (MedMOLE) that improves the comprehension of microarray experimental results by grouping co-regulated genes on the basis of the informational content of MEDLINE documents. The tool relies on two components: a gene name extractor and a mining algorithm. The name extractor is based on existing dictionaries of gene names and aliases. The mining algorithm analyses the co-occurrences of words in the selected documents in order to automatically interpret the context, identify where the gene names appear, and map documents/genes into functional classes. Microarray transcriptional profiling is a powerful tool used in the study of transcriptional control mechanisms. An important point in the analysis of microarray data is the identification of hidden correlations between the differentially expressed genes generated upon some kind of cell stimulus. Functional annotation is an important topic for microarray data mining, however this is quite limited for complex organisms (e.g. H. sapiens, M. musculus) where a limited number of genes are well characterized and annotated. However, functional data are rapidly accumulating in the scientific literature and most of them are collected by MEDLINE, a database that contains over 11,000,000 biomedical journal citations. A microarray analysis usually generates few hundred of differentially expressed genes and, after statistical validation of the data and transcription profiles clustering, biologists try to identify genes functionally correlated by scientific literature analysis. Even if some tools have been recently developed to simplify information extraction on the MEDLINE database, reading every article requires too much time and labor. Therefore, it is necessary to have some kind of intelligent information extracting system that recognizes gene names inside the texts. The analysis of text documents (e.g. MEDLINE abstracts) can be approached by two different points of view: text mining and information extraction (I.E.). The former aims at the automatic identification of groups of documents that share the same patterns of words, and thus refer to the same topic or theme. The latter aims at providing a structured representation of the textual information and requires a pre-definition of entities and relationships to be looked for inside texts. Thus while the text mining algorithms are general purpose, the information extraction algorithms are specific to the application. Furthermore, the text mining approach is explorative and enables the discovery of new concepts and relations while information extraction only extracts those elements that have already been defined. These two approaches can be integrated: information extraction tools generate databases that can be analyzed using data mining techniques, and, on the other side, text mining tools might take advantage of specific domain information extracted using I.E. techniques. MedMOLE takes advantage of text mining techniques, and simplifies the extraction of functional knowledge by literature abstracts directly/indirectly related to differentially expressed genes identified by microarray technology. Sponsors: This work was partially supported by PRIN 2001 and FIRB 2002 grants. | experimental, extractor, function, functional, gene, algorithm, cell, characteristic, class, dna, informational, literature, mechanism, medline, medline interfaces, microarray, mining, organism, stimulus, technology, transcriptional | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21258 | SCR_001848 | MedMOLE | 2026-09-05 06:24:40 | 1 | |||||||||
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AutDB Resource Report Resource Website 50+ mentions |
AutDB (RRID:SCR_001872) | AutDB | data or information resource, data repository, database, service resource, storage service resource | Curated public database for autism research built on information extracted from the studies on molecular genetics and biology of Autism Spectrum Disorders (ASD). The genetic information includes data from linkage and association studies, cytogenetic abnormalities, and specific mutations associated with ASD. New gene submissions are welcome. Modules: * Human Gene: thoroughly annotated list of genes that have been studied in the context of autism, with information on the genes themselves, relevant references from the literature, and the nature of the evidence. Uniquely, SFARI Gene incorporates information on both common and rare variants. * Animal Model: information about lines of genetically modified mice that represent potential models of autism. This information includes the nature of the targeting construct, the background strain and, most importantly, a thorough summary of the phenotypic features of the mice that are most relevant to autism. * Protein Interaction (PIN): compilation of all known direct protein interactions for those gene products implicated in autism. It presents both graphical and tabular views of interactomes, highlighting connections between autism candidate genes. Each protein interaction is manually verified by consultation with the primary reference. * Copy Number Variant (CNV): a parallel resource providing genetic information about all known copy number variants linked to autism. * Gene Scoring: includes a "score" for each autism candidate gene, based on an assessment of the strength of human genetic evidence. | duplication, gene, genetic syndrome, genetic variation, allelic, autism, autism spectrum disorder, deletion, molecular function, molecular genetics, single-gene disruption, genetic association, genetic variation, allelic variant, copy number variant, cytogenetic, disruption, idiopathic asd, monogenic, mutation, polymorphism, human, animal model, mouse, protein interaction, sfari gene, phenotype, protein interaction, gene scoring, systems biology |
is listed by: NIF Data Federation is listed by: 3DVC is related to: Integrated Manually Extracted Annotation has parent organization: SFARI - Simons Foundation Autism Research Initiative |
Autism Spectrum Disorder, Autism | MindSpec: Informatics for Neurodevelopmental Conditions | PMID:19015121 | Free, Freely available | nif-0000-02587 | http://www.mindspec.org/products/autdb/, https://gene.sfari.org/autdb/ | http://autism.mindspec.org/autdb/ | SCR_001872 | AutDB - An Interface to Autism Research, Simons Foundation Autism Research Initiative Gene: Autism Database, SFARI Gene: AutDB, SFARI Gene, AutDB: a Genetic Database for Autism Spectrum Disorders | 2026-09-05 06:24:40 | 64 | ||
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ASTRAL Compendium for Sequence and Structure Analysis Resource Report Resource Website 10+ mentions |
ASTRAL Compendium for Sequence and Structure Analysis (RRID:SCR_001886) | ASTRAL | data or information resource, data processing software, data storage software, database, software application, software resource | It provides databases and tools useful for analyzing protein structures and their sequences. It is partially derived from, and augments the SCOP: Structural Classification of Proteins database, a database created by manual inspection and abetted by a battery of automated methods, aims to provide a detailed and comprehensive description of the structural and evolutionary relationships between all proteins whose structure is known. Most of the resources provided here depend upon the coordinate files maintained and distributed by the Protein Data Bank. Sponsors: This work is supported by grants from the NIH (1-P50-GM62412, 1-K22-HG00056) and the Searle Scholars Program (01-L-116), and by the US Department of Energy under contract DE-AC03-76SF00098. | gene, amino acid, homology, protein sequence, protein structure | has parent organization: University of California at Berkeley; Berkeley; USA | PMID:10592239 | Free, Available for download, Freely available | nif-0000-02580 | SCR_001886 | ASTRAL Compendium for Sequence and Structure Analysis, The ASTRAL Compendium for Sequence and Structure Analysis | 2026-09-05 06:24:41 | 32 | ||||||
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Aspergillus Genomes Resource Report Resource Website |
Aspergillus Genomes (RRID:SCR_001880) | Aspergillus Genomes | analysis service resource, data analysis service, data or information resource, database, production service resource, service resource | A resource for viewing annotated genes arising from various Aspergillus sequencing and annotation projects, resulting from the merging of Central Aspergillus Data REpository (CADRE) and The Aspergillus Website, which took place in June 2008. The principal role of CADRE is to aid the Aspergillus research community by managing Aspergillus genome data and by providing visualization tools, ranging from relatively simple annotation displays to more complex data integration displays. In contrast, The Aspergillus Website provides a range of information to the medical community (i.e., clinicians, patients and scientists) regarding the genus Aspergillus and the diseases, such as Aspergillosis, that it can cause. CADRE has been implemented using the Ensembl v22 suite. This suite comprises: * a database schema, which has been devised for storing annotated eukaryotic genomes. The schema is implemented with the MySQL relational database management system. * several specialized programming modules for building interfaces (i.e., BioPerl and Ensembl API modules). * a series of programs (i.e., Perl CGI scripts using the API modules) for viewing genomic data within a web browser., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. | genome, eukaryotic genome, gene, gene annotation, aspergillosis, aspergillus, pathway, annotation, sequence, metabolic pathway, genomics, clinical, strain, dna, peptide, blast | Fungal Research Trust | PMID:19039001 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-02577, r3d100011253 | https://doi.org/10.17616/R3005P | SCR_001880 | 2026-09-05 06:24:41 | 0 | ||||||
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DAVID Resource Report Resource Website 10000+ mentions |
DAVID (RRID:SCR_001881) | DAVID | data access protocol, data or information resource, database, software resource, web service | THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis. | functional domain, annotation, motif, protein, ontology enrichment, gene, high-throughput, functional classification, functional annotation, clustering, genome, pathway, gene-disease association, interaction, functional domain, motif, visualization, FASEB list |
is listed by: OMICtools is listed by: 3DVC is listed by: LabWorm is listed by: SoftCite is related to: Gene Ontology is related to: BioCarta Pathways is related to: KEGG has parent organization: NCI-Frederick |
NCI ; NIAID NO1-CO-56000 |
PMID:19131956 PMID:12734009 PMID:35325185 PMID:22543366 PMID:17980028 PMID:17576678 |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-30408, OMICS_02220, nif-0000-10451, SCR_003033 | http://david.abcc.ncifcrf.gov/ | SCR_001881 | DAVID Bioinformatics Resources, Visualization and Integrated Discovery Bioinformatics Resources, Database for Annotation Visualization and Integrated Discovery, The Database for Annotation, The Database for Annotation Visualization and Integrated Discovery Bioinformatics Resources | 2026-09-05 06:24:41 | 20855 | ||||
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GATK Resource Report Resource Website 10000+ mentions |
GATK (RRID:SCR_001876) | GATK | data analysis software, data processing software, software application, software library, software resource, software toolkit | A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software) | gene, genetic, genomic, next-generation resequencing, bio.tools |
is used by: Halvade Somatic is listed by: OMICtools is listed by: Genetic Analysis Software is listed by: bio.tools is listed by: Debian is listed by: SoftCite is related to: SnpEff is related to: GATK HaplotypeCaller is related to: GATK VariantFiltration has parent organization: Broad Institute |
PMID:21478889 | Free, Available for download, Freely available | nlx_154324, OMICS_00286, biotools:gatk | http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit, https://bio.tools/gatk | SCR_001876 | Genome Analysis ToolKit | 2026-09-05 06:24:40 | 18211 | |||||
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University of Utah Genetic Science Learning Center - Learn Genetics Resource Report Resource Website 1+ mentions |
University of Utah Genetic Science Learning Center - Learn Genetics (RRID:SCR_001910) | Learn.Genetics, Learn Genetics | data or information resource, narrative resource, slide, training material, training resource, video resource | Educational resources that provide accurate and unbiased information about topics in genetics, bioscience and health for global and local audiences. They are jargon-free, target multiple learning styles, and often convey concepts through animation and interactivity. The Genetic Science Learning Center is a science and health education program located in the midst of the bioscience research being carried out at the University of Utah. Our mission is making science easy for everyone to understand. * Two websites, available free of charge to Internet users worldwide: ** Learn.Genetics delivers educational materials on genetics, bioscience and health topics. They are designed to be used by students, teachers and members of the public. The materials meet selected US education standards for science and health. ** Teach.Genetics provides resources for K-12 teachers, higher education faculty, and public educators. These include PDF-based Print-and-Go™ activities, unit plans and other supporting resources. The materials are designed to support and extend the materials on Learn.Genetics. *Professional development programs that update K-16 teachers' expertise in bioscience and health topics as well as prepare them to implement the materials on our websites. * Community programs that engage with diverse communities in discussions about genetics and health, and in developing culturally and linguistically-appropriate educational materials. Some topics in genetics and bioscience research are controversial. The Center does not take sides in political or ethical controversies. Rather, our goal is to provide comprehensive information that promotes a lively discussion of these topics, so that individuals can arrive at their own informed decisions. | gene, dna, protein, education, genetics, science, bioscience, health, teacher, student, public, professional development, k-12, undergraduate, lesson plan, heredity, genetic trait, cell, molecule, stem cell, cloning, gene therapy, transgenic mouse, epigentics, addiction, genetic variation |
has parent organization: University of Utah; Utah; USA is parent organization of: New Science of Addiction: Genetics and the Brain |
NIH Office of the Director R25OD021903 | You are granted a revocable license to download and print hard copy versions of the material contained on the site for your personal, Educational and noncommercial use, Provided you do not modify or delete any copyright or other notice that appears on the material you download or print. | nif-0000-10482 | http://learns.genetics.utah.edu/ | SCR_001910 | University of Utah Genetic Science Learning Center, Genetic Science Learning Center - Learn.Genetics, Genetic Science Learning Center, Genetic Science Learning Center - Learn Genetics | 2026-09-05 06:24:41 | 9 | |||||
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MouseCyc Resource Report Resource Website 10+ mentions |
MouseCyc (RRID:SCR_001791) | MouseCyc | analysis service resource, data analysis service, data or information resource, database, production service resource, service resource | A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database. | energy production, biosynthesis, cell, cellular, degradation, detoxification, metabolism, mouse, physiological, enzymatic reaction, gene, disease, genome, metabolic pathway, pathway, compound, enzymatic reaction, protein, rna, reaction, blast, human, mammal, genetic, genomic |
is related to: Mouse Genome Informatics (MGI) is related to: Gene Ontology has parent organization: Jackson Laboratory |
NHGRI HG003622 | PMID:19682380 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-10303 | SCR_001791 | MouseCyc database, Mouse Genome Informatics: MouseCyc database | 2026-09-05 06:24:39 | 10 | |||||
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Arabidopsis Hormone Database Resource Report Resource Website 10+ mentions |
Arabidopsis Hormone Database (RRID:SCR_001792) | AHD, AHD2.0 | controlled vocabulary, data or information resource, data repository, database, ontology, service resource, storage service resource | Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions. | arabidopsis thaliana, hormone, hormone function, hormone gene, phytohormone, abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid, salicylic acid, microarray, phenotype, gene, mirna prediction, expression, mutant, blast, orthologue, mirna splicing site, root, cotyledon, leaf, hypocotyl, stem, flower, silique, seed, embryo, stress, morphology, plant, hormone, regulatory gene, mutant, transgenic, annotation, data analysis service |
is related to: Gene Ontology has parent organization: Peking University; Beijing; China |
National Natural Science Foundation of China 30625003; National Natural Science Foundation of China 30730011; Ministry of Science and Technology of China 2009CB119101; Ministry of Education of China ED20060047 |
PMID:21045062 PMID:19015126 |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-02559 | SCR_001792 | Arabidopsis Hormone Database 2.0 | 2026-09-05 06:24:39 | 28 |
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