Tools   Select Another Resource Report Type

http://www.rhea-db.org/

Manually annotated reaction database where all reaction participants (reactants and products) are linked to the ChEBI database (Chemical Entities of Biological Interest) which provides detailed information about structure, formula and charge. Rhea provides built-in validations that ensure both elemental and charge balance of the reactions. The database has been populated with the reactions found in the Enzyme Commission (EC) list (and in the IntEnz and ENZYME databases), extending it with additional known reactions of biological interest. While the main focus of Rhea is enzyme-catalyzed reactions, other biochemical reactions are also included. Rhea is a manually annotated resource and it provides: stable reaction identifiers for each of its reactions; directionality information if the physiological direction of the reaction is known; the possibility to link several reactions together to form overall reactions; extensive cross-references to other resources including enzyme-catalyzed and other metabolic reactions, such as the EC list (in IntEnz), KEGG, MetaCyc and UniPathway; and chemical substructure and similarity searches on compounds in Rhea.

Proper citation: RHEA (RRID:SCR_004713) Copy   

•   Source: SciCrunch Registry
  

http://scicrunch.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26, 2019.An international Non-Profit Organization that advocates Open Access for never-before-published research papers on the web and provides Self-Archiving platform to enable better knowledge sharing in a way that''s easy to publish. They collect scientific material (not only publications), e.g., Journal Articles, Theses or Dissertations, Departmental Bulletin Papers, Conference Papers, Presentations, Books, Technical Reports, Research Papers, Articles, Preprints, Learning Materials, Others. If you have such a paper and would like to add a Creative Commons license to your work, or if your working organization has no Institutional Repository (IR), Open your archives to spread them to the world. How to use: 1. Sign in with Twitter 2. Select PDF and add a Creative Commons license 3. Publish and Share on Social Media Video tutorial: http://myopenarchive.org/whatsmyoa

Proper citation: MyOpenArchive (RRID:SCR_004917) Copy   

•   Source: SciCrunch Registry
  

http://birdgenenames.org/cgnc/

International group of researchers interested in providing standardized gene nomenclature for chicken genes. A Chicken Gene Annotation Tool is available from CGNC-UK which assigns chicken nomenclature based on predicted orthology to human genes. The CGNC-US database includes CGNC-UK information and adds manually biocurated from biocurators and interested contributors. A Human Chicken Ortholog Predictions Search is available. Both resources are part of a united CGNC effort and nomenclature data is shared and co-ordinated between these two resources. They strongly encourage researchers with domain knowledge to participate in this nomenclature effort by requesting a login and providing gene nomenclature for their genes of interest. Please contact them for further information or assistance. The AGNC works in conjunction with public resources such as NCBI and Ensembl and in consultation with existing nomenclature committees, including the Chicken Gene Nomenclature Committee (CGNC). The Avian and Chicken nomenclature efforts are co-ordinated and chicken data is shared between these two groups.

Proper citation: Chicken Gene Nomenclature Consortium (RRID:SCR_004966) Copy   

•   Source: SciCrunch Registry
  

http://www.genet.sickkids.on.ca/cftr/

Collection of mutations in CFTR gene for international cystic fibrosis genetics research community. Provides up to date information about individual mutations in CFTR gene. All known CFTR mutations and sequence variants have been converted to standard nomenclature recommended by Human Genome Variation Society. On line process for submission of new mutations has been added.While they continue to ensure quality of data, they urge international community to give them feedback and suggestions. Clinical information in this database relates only to details of discovery of specific mutations. As part of 2010 upgrade, CFTR1 joined new project called CFTR2 - Clinical and Functional TRanslation of CFTR. Links to CFTR2 for many mutations in CFTR1 will provide up-to-date summaries of genotype-phenotype information from patient registries around the world.

Proper citation: Cystic Fibrosis Mutation Database (RRID:SCR_000685) Copy   

•   Source: SciCrunch Registry
  

http://www.camarades.info/index_files/Protocols.html

A site for sharing meta-analysis protocols for translational neuroscience research. Protocols for systematic review of in vivo data modelling human neurological disease. Making the protocol for your systematic review available to the community has a number of benefits; it provides evidence that prespecified analyses were indeed prespecified; allows others to comment on your approach; provides examples for others planning such reviews; and can help you identify if other reviews in similar areas are already in progress. This site was created to foster collaboration.

Proper citation: CAMARADES Protocols for Systematic Reviews of Animal Studies (RRID:SCR_008970) Copy   

•   Source: SciCrunch Registry
  

http://link.springer.com/article/10.1007%2Fs11357-003-0002-y

A database that stores information on the biomolecules which are modulated during aging and by caloric restriction (CR). To enhance its usefulness, data collected from studies of CR''''s anti-oxidative action on gene expression, oxidative stress, and many chronic age-related diseases are included. AgingDB is organized into two sections A) apoptosis and the various mitochondrial biomolecules that play a role in aging; B) nuclear transcription factors known to be_sensitive to oxidative environment. AgingDB features an imagemap of biomolecular signal pathways and visualized information that includes protein-protein interactions of biomolecules. Authorized users can submit a new biomolecule or edit an existing biomolecule to reflect latest developments.

Proper citation: AgingDB (RRID:SCR_010226) Copy   

•   Source: SciCrunch Registry
  

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

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

Proper citation: ClinVar (RRID:SCR_006169) Copy   

•   Source: SciCrunch Registry
  

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

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

Proper citation: miRecords (RRID:SCR_013021) Copy   

•   Source: SciCrunch Registry
  

http://www.mrc-lmb.cam.ac.uk/genomes/dolop/

DOLOP is an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. This website along will have additional information on the biosynthetic pathway, supplementary material and other related figures. DOLOP also contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. Additionally, the website features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins.

Proper citation: DOLOP: A Database of Bacterial Lipoproteins (RRID:SCR_013487) Copy   

•   Source: SciCrunch Registry
  

http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp

A database for facilitating the search for drug Absorption, Distribution, Metabolism, Excretion (ADME) associated proteins. It contains information about known drug ADME associated proteins, functions, similarities, substrates / ligands, tissue distributions, and other properties of the targets. Associated references are also included. Drug absorption, distribution, metabolism and excretion (ADME) often involve interaction of a drug with specific proteins. Knowledge about these ADME-associated proteins is important in facilitating the study of the molecular mechanism of disposition and individual response as well as therapeutic action of drugs. It is also useful in the development and testing of pharmacokinetics prediction tools. Several databases describing specific classes of ADME-associated proteins have appeared. A new database, ADME-associated proteins (ADME-AP), is introduced to provide comprehensive information about all classes of ADME-associated proteins described in the literature including physiological function of each protein, pharmacokinetic effect, ADME classification, direction and driving force of disposition, location and tissue distribution, substrates, synonyms, gene name and protein availability in other species. Cross-links to other databases are also provided to facilitate the access of information about the sequence, 3D structure, function, polymorphisms, genetic disorders, nomenclature, ligand binding properties and related literatures of each protein. ADME-AP currently contains entries for 321 proteins and 964 substrates. ADME Class Based on their respective role of pharmacokinetics, ADME-associated proteins can be classified into four categories: A: This Category includes proteins involved in the absorption or re-absorption of drugs into systemic system. D: This category includes proteins responsible for facilitating the distribution of drugs from the systemic system to the target sites or away from the target sites back to the systemic system. Certain plasma proteins and intracellular binding proteins may alter free drug concentration by acting as drug storage depot. These proteins thus play a regulatory role in drug distribution and they are thus included in Category D. Based on their role in drug distribution, proteins in this category can be further divided into three groups D1, D2, and D3. The first group D1 includes transporters capable of transporting chemicals across membranes of various tissue barriers from the systemic system into the target sites. Blood-brain barrier and placenta barrier are examples of tissue barrier. Proteins in the second group D2 are responsible for transporting drugs back into the systemic system. Proteins in the third group D3 mainly function as drug storage depot. These include ligand binding proteins in plasma and intracellular proteins. M: Proteins in category M are drug-metabolizing enzymes. These enzymes can be further divided into two separate groups M1 and M2, according to whether the corresponding enzymatic reaction is phase I or phase II. E: This category E includes proteins that enable the excretion or presystemic elimination of drugs. Some proteins belong to more than one category: e.g. P-glycoprotein both limits intestinal absorption and excludes drugs from the brain back to the blood. It thus belongs to both Category E and D. For those proteins capable of transporting natural substrates without literature report of interaction with a drug, a postfix potential is attached to their respective classification to indicate that their specific role in ADME is yet to be confirmed. Use of ADME-AP for commercial purposes is not allowed.

Proper citation: Drug ADME Associated Protein Database (RRID:SCR_013501) Copy   

•   Source: SciCrunch Registry
  

http://fluency.talkbank.org/

Database for study of development of fluency in both normal and disordered populations. Participants include normally-developing monolingual and bilingual children, children with disfluencies (CWD), adults with disfluencies (AWSD), and second language learners.

Proper citation: FluencyBank (RRID:SCR_016313) Copy   

•   Source: SciCrunch Registry
  

http://research.bmh.manchester.ac.uk/bryce/amber

Assisted model building with energy refinement parameter database. Family of force fields for molecular dynamics of biomolecules. Collection of equations and associated constants designed to reproduce molecular geometry and selected properties of tested structures.

Proper citation: AMBER parameter database (RRID:SCR_018815) Copy   

•   Source: SciCrunch Registry
  

https://bioregistry.io

Open source, community curated registry, meta-registry, and compact identifier resolver. Used for unifying identification of biomedical entities through integrative, open,community driven metaregistry. The registry contains metadata about ontologies, controlled vocabularies, and resources including their preferred prefix, name, description, homepage, mappings to other registries, and more.

Proper citation: Bioregistry (RRID:SCR_022586) Copy   

•   Source: SciCrunch Registry
  

https://github.com/ncbi/pgap

Software tool as NCBI prokaryotic genome annotation pipeline. Used to annotate both complete genomes and draft genomes comprising multiple contigs. Integrated into NCBI infrastructure and processes, and uses modular software framework, GPipe, developed at NCBI for execution of all annotation tasks, from fetching of raw and curated data from public repositories through sequence alignment and model based gene prediction, to submission of annotated genomic data to public NCBI databases.

Proper citation: Prokaryotic Genomes Automatic Annotation Pipeline (RRID:SCR_021329) Copy   

•   Source: SciCrunch Registry
  

http://aphasia.talkbank.org/

Shared database of multimedia interactions for the study of communication in aphasia.Access to the data in AphasiaBank is password protected and restricted to members of the AphasiaBank consortium group.

Proper citation: AphasiaBank (RRID:SCR_016317) Copy   

•   Source: SciCrunch Registry
  

https://www.mirri.org/

Microbial stock center. Collaborative platform for the pan-European research infrastructure for microbial resources. Provides access to microorganisms, their derivatives, associated data and services for research, development and application.

Proper citation: MIRRI (RRID:SCR_016461) Copy   

•   Source: SciCrunch Registry
  

http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

•   Source: SciCrunch Registry
  

http://zfin.org

Model organism database that serves as central repository and web-based resource for zebrafish genetic, genomic, phenotypic and developmental data. Data represented are derived from three primary sources: curation of zebrafish publications, individual research laboratories and collaborations with bioinformatics organizations. Data formats include text, images and graphical representations.Serves as primary community database resource for laboratory use of zebrafish. Developed and supports integrated zebrafish genetic, genomic, developmental and physiological information and link this information extensively to corresponding data in other model organism and human databases.

Proper citation: Zebrafish Information Network (ZFIN) (RRID:SCR_002560) Copy   

•   Source: SciCrunch Registry
  

http://www.nitrc.org/projects/masimatlab/

This repository stores and provides opportunities for collaboration through Matlab code, libraries, and configuration information for projects in early stage development. The MASI research laboratory concentrates on analyzing large-scale cross-sectional and longitudinal neuroimaging data. Specifically, they are interested in population characterization with magnetic resonance imaging (MRI), multi-parametric studies (DTI, sMRI, qMRI), and shape modeling.

Proper citation: MASIMatlab (RRID:SCR_009506) Copy   

•   Source: SciCrunch Registry
  

https://princessmargaretcancerbiobank.com/

Core offers biobanking services and diverse inventory of biospecimens in the field of Oncology. Offers prospective protocol specific banking tailored to your research needs, including patient eligibility, screening, consenting, biospecimen procurement, handling, and processing, clinical data annotation, short and long-term sample storage, and shipping.

Proper citation: University Health Network Princess Margaret Cancer Biobank Core Facility (RRID:SCR_027522) Copy   

•   Source: SciCrunch Registry