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http://www.evidenceontology.org

A controlled vocabulary that describes types of scientific evidence within the realm of biological research that can arise from laboratory experiments, computational methods, manual literature curation, and other means. Researchers can use these types of evidence to support assertions about research subjects that result from scientific research, such as scientific conclusions, gene annotations, or other statements of fact. ECO comprises two high-level classes, evidence and assertion method, where evidence is defined as a type of information that is used to support an assertion, and assertion method is defined as a means by which a statement is made about an entity. Together evidence and assertion method can be combined to describe both the support for an assertion and whether that assertion was made by a human being or a computer. However, ECO can not be used to make the assertion itself; for that, one would use another ontology, free text description, or other means. ECO was originally created around the year 2000 to support gene product annotation by the Gene Ontology. Today ECO is used by many groups concerned with provenance in scientific research. ECO is used in AmiGO 2

Proper citation: ECO (RRID:SCR_002477) Copy   

•   Source: SciCrunch Registry

http://dynamine.ibsquare.be/submission/

An NMR based method for protein folding prediction. Users can enter a UniProt identifier, FASTA sequences, or upload a file containing FASTA sequences and results are returned., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DynaMine (RRID:SCR_014559) Copy   

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http://purl.bioontology.org/ontology/OntoVIP

Ontology that describes the content of the models used in medical image simulation developed in the context of the Virtual Imaging Platform project (VIP), a french project aiming at sharing medical image simulation resources. This ontology can be used to annotate such models in order to highlight the different entities that are present in the 3D scene to be imaged, i.e. anatomical structures, pathological structures, foreign bodies, contrast agents etc. The model allows also to associate to these entities information about their physical qualities, which are used in the medical image simulation process (to mimick physical phenomena involved in CT, MR, US and PET imaging). This ontology partly relies on the OntoNeuroLOG ontology (ONL-DP ONL-MR-DA), as well as PATO, RadLex, FMA and ChEBI.

Proper citation: Medical image simulation (RRID:SCR_010355) Copy   

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http://purl.bioontology.org/ontology/ONL-MSA

Ontology that is a module of the OntoNeuroLOG ontology that covers the field of mental state assessments, i.e. instruments, instrument variables, assessments, and resulting scores, developed in the context of the NeuroLOG project, a french project aiming at integrating distributed heterogeous resources in neuroimaging. It includes a generic domain core ontology, that provides a general model of such entities and a general taxonomy of behavioural, neurosychological and neuroclinical instruments, that can be easily extended to model any particular kind of instrument. It also includes such extensions for 8 relatively standard instruments, namely: (1) the Beck-depression-inventory-(BDI-II), (2) the Expanded-Disability-Status-Scale, (3) the Controlled-oral-word-association-test, (4) the Free-and-Cued-Selective-Reminding-Test-with-Immediate-Recall-16-item-version-(The-Grober-and-Buschke-test), (5) the Mini-Mental-State, (6) the Stroop-color-and-word-test, (7) the Trail-making-test-(TMT), (8) the Wechsler-Adult-Intelligence-Scale-third-edition, (9) the Clinical-Dementia-Rating-scale, (10) the Category-verbal-fluency, (11) the Rey-Osterrieth-Complex-Figure-Test-(CFT).

Proper citation: Mental State Assessment (RRID:SCR_010357) Copy   

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https://omictools.com/3omics-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented October 19, 2016. A web tool for visualizing and integrating multiple inter- or intra-transcriptomic, proteomic, and metabolomic human data. 3Omics generates inter-omic correlation networks to visualize relationships in data with respect to time or experimental conditions for transcripts, proteins and metabolites.

Proper citation: 3Omics (RRID:SCR_014678) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/MSV

An ontology for metagenome sample metadata that mainly defines predicates.

Proper citation: Metagenome Sample Vocabulary (RRID:SCR_010358) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/TGMA

A structured controlled vocabulary of the anatomy of mosquitoes.

Proper citation: Mosquito Gross Anatomy Ontology (RRID:SCR_003839) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CPTAC

A basic ontology which describes the proteomics pipeline infrastructure for CPTAC project

Proper citation: CPTAC Proteomics Pipeline Infrastructure Ontology (RRID:SCR_006945) Copy   

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http://genecards.weizmann.ac.il/genenote/

THIS RESOURCE IS NO LONGER IN SERVICE, documented June 14, 2013. GeneNote is a database of human genes and their expression profiles in healthy tissues. It is based on Weizmann Institute of Science DNA array experiments, which were performed on the Affymetrix HG-U95 set A-E. It offers: An expression profile (tissue vector) for each gene in the human genome Gene and tissue clustering based on expression profiles A full genome ranking procedure according to the gene''s tendency for tissue specificity, from tissue-specific to housekeeping genes.

Proper citation: GeneNote (RRID:SCR_007679) Copy   

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http://research.nhgri.nih.gov/histones/

Histone Database is a database of histones and their corresponding sequences. Sequence- and text-based searches were performed on NCBI's redundant and non-redundant (nr) peptide sequence databases. These databases are derived from GenBank, EMBL, and DDBJ translated DNA coding regions, plus protein sequences from the PDB (Protein Data Bank), SWISS-PROT, the PIR (Protein Information Resource), and the PRF (Protein Research Foundation). :Users can search by keyword, sequence fragment, category, organism, and redundancy of the set.

Proper citation: Histone Database (RRID:SCR_007711) Copy   

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http://www.biocheminfo.org/klotho/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. A database of biochemical compound information. All files are available for download, and all entries are cataloged by accession number. Klotho is part of a larger attempt to model biological processes, beginning with biochemistry.

Proper citation: Klotho: Biochemical Compounds Declarative Database (RRID:SCR_007714) Copy   

•   Source: SciCrunch Registry

http://urgi.versailles.inra.fr/Genefarm/

GeneFarm is a database of structural and functional annotation of plant gene and protein families. The goal of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for plant nuclear genes and gene products and to enter them into added-value database. The improved annotation will allow better data mining of the plant genomes (mainly Arabidopsis thaliana), and more secure planning and design of experiments. It is also a necessary step for building knowledge management tools for integrating plant genomic data, either for plant breeding or to get a broader interactive view of plant biological processes, like gene interaction networks. This re-annotation project, launched is mainly focused on gene families. A complete annotation pipeline using the most efficient prediction tools has been defined. The involved partners, each contributing with genes from his/her field of expertise, have exhaustively annotated families of homologous genes. A database named GeneFarm (Gene Families for Arabidopsis Management) gathers all these expert-curated annotations of plant gene families. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Prot.

Proper citation: GeneFarm (RRID:SCR_007674) Copy   

•   Source: SciCrunch Registry

http://caps.ncbs.res.in/gendis/home.html

Genomic Distribution of structural Superfamilies identifies and classifies evolutionary related proteins at the superfamily level in whole genome databases. GenDiS has been curated in direct correspondence with SCOP and represents 4001 highly resolved domains in 1194 structural superfamilies across protein sequence databases. Sequences showing reliable homology to entries in SCOP and PASS2 databases have been obtained from the non-redundant protein sequence database and aligned. Similar alignments of the superfamily members are provided in the genome level. GenDiS provides a platform for cross genome comparison at the superfamily level. GenDis relates proteins sequence information across all strata of taxonomy. One may navigate through the database to obtain structural homologues across different levels in taxonomic classification. The nomenclature of the various genomes and their hierarchy is in direct correspondence with the taxonomy database maintained at the NCBI. Sequence homologues for the various structural members are obtained from the non-redundant protein sequence database employing sensitive sequence search methods. Multiple approaches such as PSI-BLAST, HMMsearch of the HMMer suite and an interacting motif constrained PHI-BLAST have been employed to identify homologues in the sequence databases.

Proper citation: Genomic Distribution of structural Superfamilies (RRID:SCR_007670) Copy   

•   Source: SciCrunch Registry

http://genecards.weizmann.ac.il/geneannot/

GeneAnnot provides a revised and improved annotation of Affymetrix probe-sets from HG-U95, HG-U133 and HG-U133 Plus2.0. Probe-sets are related to GeneCards genes, by direct sequence comparison of probes to GenBank, RefSeq and Ensembl mRNA sequences, while assigning sensitivity and specificity scores to each probe-set to gene match. Where such matches are not found, probe-sets are annotated by their relation to GenBank mRNA sequences and UniGene clusters. The results are integrated with the GeneCards, GeneLoc and GeneNote databases. HG-U95, HG-U133, HG-U133

Proper citation: GeneAnnot (RRID:SCR_007673) Copy   

•   Source: SciCrunch Registry

http://www.hepseq.org/Public/Web_Front/main.php

HepSEQ is the International Repository for Hepatitis B Virus Strain Data. It is web-accessible, quality-based, molecular, clinical and epidemiological database for hepatitis B infection and provides a tool for the research community or for those involved in hepatitis B case management. This database currently has 1012 patient records and 1253 viral sequences. The quality of all submitted sequences is checked. The tools provided include: SeqMatch: search the database for matching sequences Genotyper: genotype HBV strains (based on HBV surface antigen genes) Gene Mutation: display the sequences that contain mutations in HBV coding regions Mutation Annotator: annotate sequences for mutation known to be associated with anti-viral resistance This web database development is funded by the UK Department of Health is curated and is hosted by the Health Protection Agency.

Proper citation: Hepatitis Virus B Database (RRID:SCR_007705) Copy   

•   Source: SciCrunch Registry

https://omictools.com/heg-db-tool

Genomic database that includes prediction of which genes are highly expressed in prokaryotic complete genomes under strong translational selection.

Proper citation: Highly Expressed Genes Database (HEG-DB) (RRID:SCR_007704) Copy   

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http://www.compbio.dundee.ac.uk/kinomer

Kinomer is a multilevel HMM library that models these protein kinase groups. It allows accurate identification of protein kinases and classification to the appropriate kinase group. Profile hidden Markov models (HMMs) are statistical descriptions of sequence conservation from multiple sequence alignments, and have been shown to outperform standard pairwise sequence comparison methods, both in terms of sensitivity and specificity. HMMs form the basis of protein family and domain description libraries such as SUPERFAMILY and Pfam.

Proper citation: Kinomer (RRID:SCR_007707) Copy   

•   Source: SciCrunch Registry

http://www.genatlas.org/

GENATLAS contains relevant information with respect to gene mapping and genetic diseases. GENATLAS compiles the information relevant to the mapping efforts of the Human Genome Project. This information is collected from more than 48,000 articles in the literature, collected in more than 870 reviews. The articles are daily analyzed by annotators to update the GENATLAS database. Only the objects with a known cytogenetic location are retained. GENATLAS repertories three kinds of objects Genes database ( more than 21.000 entries) Phenotypes database ( 4104 entries , 2000 cloned) References database linked to the two previous ( more than 48000 entries)

Proper citation: GenAtlas (RRID:SCR_007669) Copy   

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http://www.ncrna.org/frnadb

fRNAdb is a database of comprehensive non-coding RNA (ncRNA) sequences including known (or previously reported) ncRNAs, which are acquired from other sequence databases, and ncRNA sequences reported by the joint research groups of the Functional RNA Project. It is funded by the New Energy and Industrial Technology Development Organization.

Proper citation: functional RNAdb (RRID:SCR_007664) Copy   

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http://flysnp.imp.univie.ac.at

This project aims to provide the information and technical resources to support high-throughput positional cloning in Drosophila melanogaster. These resources include a high-density genome-wide map of single nucleotide polymorphisms (SNPs), and inexpensive, high-throughput assays for SNP genotyping. The specific aims were as follows: 1. To establish a map of >2200 SNP marker loci in the Drosophila genome. These SNP markers have been identified in several commonly used genetic strains. The FlySNP project identified SNP markers within the sequenced, euchromatic regions of the X, 2nd and 3rd chromosomes. The average distance between SNPs is about 50 kb. 2. To establish robust, high-throughput assays for SNP genotyping. Assays have been established using PCR, microarray and mass-spectrometry methods. The tag-array mini-sequencing (TAMS) approach has proven to be an especially fast and reliable method for SNP genotyping.

Proper citation: FLYSNP (RRID:SCR_007663) Copy   

•   Source: SciCrunch Registry