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https://github.com/Ensembl

Public database that stores areas of genome that differ between individual genomes (variants) and, where available, associated disease and phenotype information. Different types of variants for several species: single nucleotide polymorphisms (SNPs), short nucleotide insertions and/or deletions, and longer variants classified as structural variants (including CNVs). Effects of variants on the Ensembl transcripts and regulatory features for each species are predicted. You can run same analysis on your own data using Variant Effect Predictor. These data are integrated with other data sources in Ensembl, and can be accessed using the API or website. For several different species in Ensembl, they import variation data (SNPs, CNVs, allele frequencies, genotypes, etc) from a variety of sources (e.g. dbSNP). Imported variants and alleles are subjected to quality control process to flag suspect data. In human, they calculate linkage disequilibrium for each variant, by population.

Proper citation: Ensembl Variation (RRID:SCR_001630) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/books/NBK5330/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.Searchable book regarding molecular imaging and contrast agents (under development, in clinical trials or commercially available for medical applications) that have in vivo data (animal or human) published in peer-reviewed scientific journals prior to June 30 of 2013. 1444 agents are currently listed and there will be no more updates. Also available is a downloadable list of FDA approved contrast agents (Latest update: January 2013) and a Molecular Imaging Probes and Contrast Agents List (MIP & CA List) created by the MICAD staff by screening the PubMed / MedLine databases and other appropriate sources of such information. Only agents used in animal or human studies yielding in vivo data were selected for inclusion in the list. The list is by no means considered complete. No one imaging modality has been given preference over the others and the omission of any agent(s) or the introduction of any errors in the list is purely unintentional. The MIP & CA List is subject to the same copyright and disclaimers as the rest of the MICAD content. The database includes, but is not limited to, agents developed for positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), ultrasound (US), computed tomography (CT), optical imaging, planar radiography, and planar gamma imaging. The information on each agent is summarized in a book chapter format containing several sections such as Background, Synthesis, in vitro studies, Animal Studies (with sub-sections: rodents, other non-human primate animals, and human primates), Human Studies, and References. In addition, the references are linked to PubMed for retrieval of the publication abstract. Also, each chapter contains links to resources at the National Center for Biotechnology Information (NCBI) and other relevant databases regarding the target of the imaging probe or contrast agent.

Proper citation: Molecular Imaging and Contrast Agent Database (RRID:SCR_006712) Copy   

•   Source: SciCrunch Registry

http://karg.cbi.pku.edu.cn

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Database of data and knowledge linking genes and chromosome regions to addiction that were extracted from reviewing more than 1,000 peer-reviewed publications from between 1976 and 2006. This list of publications included review papers on addiction selected from results of PUBMED query "(addiction OR drug abuse) AND review" as well as research papers selected from PUBMED query "(addiction OR drug abuse) AND (gene OR microarray OR proteomics OR QTL OR population association OR genetic linkage)". The data spanned multiple technology platforms including classical hypothesis-testing of single genes, identification of significantly differentially expressed genes in microarray experiments, identification of significantly differentially expressed proteins in proteomics assays, identification of addiction-vulnerable chromosome regions in animal QTL studies, genetic linkage studies, population association studies, and OMIM annotations. From each publication they collected the genes, proteins, or chromosome regions linked to addiction, as well as metadata such as species, nature of the addictive substance, studied brain regions, technology platforms, and experimental parameters. In total, they collected 2,343 items of evidence linking 1,500 human genes to addiction. Among them 396 genes were supported by two or more items of evidence. The interface supports browsing of the genes by chromosome or pathways, advanced text search by gene ID, organism, type of addictive substance, technology platform, protein domain, and/or PUBMED ID, and sequence search by BLAST similarity. All data, database schema, and MySQL commands are freely available for download.

Proper citation: Knowledgebase for Addiction Related Genes (RRID:SCR_002687) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/DRG

Gene expression data from published journal articles that test hypotheses relevant to neuroscience of addiction and addictive behavior. Data types include effects of particular drug, strain, or knock out on particular gene, in particular anatomical region. Focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data are available for query through NIF interface.Data submissions are welcome.

Proper citation: Drug Related Gene Database (RRID:SCR_003330) Copy   

•   Source: SciCrunch Registry

http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

•   Source: SciCrunch Registry