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https://scdevdb.deepomics.org/

Database for insights into single cell gene expression profiles during human developmental processes. Interactive database provides DE gene lists in each developmental pathway, t-SNE map, and GO and KEGG enrichment analysis based on these differential genes.

Proper citation: Single Cell Developmental Database (RRID:SCR_017546) Copy   

•   Source: SciCrunch Registry

https://kg.ebrains.eu/

Metadata management system built for EBRAINS. Multi modal metadata store which brings together information from different areas of Human Brain Project as well as from external partners. Graph database tracks linkage between experimental data and neuroscientific data science supporting more extensive data reuse and complex computational research.Supports rich terminologies, ontologies and controlled vocabularies. Built by design to support iterative elaborations of common standards and supports these by probabilistic suggestion and review systems.

Proper citation: EBRAINS Knowledge Graph (RRID:SCR_017612) Copy   

•   Source: SciCrunch Registry

http://circadb.hogeneschlab.org/

Database of mammalian circadian gene expression profiles. Works with link outs to Wikipedia, HomoloGene, Refseq, etc.. Open source database of circadian transcriptional profiles from time course expression experiments from mice and humans.

Proper citation: CircaDB (RRID:SCR_018078) Copy   

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http://www.loni.ucla.edu/~thompson/thompson.html

The UCLA laboratory of neuroimaging is working in several areas to enhance knowledge of anatomy, including brain mapping in large human populations, HIV, Schizophrenia, methamphetamine, tumor growth and 4d brain mapping, genetics and detection of abnormalities.

Proper citation: University of California at Los Angeles, School of Medicine: Neuro Imaging Lab of Thompson (RRID:SCR_001924) Copy   

•   Source: SciCrunch Registry

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry

http://ww2.sanbi.ac.za/Dbases.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The STACKdb is knowledgebase generated by processing EST and mRNA sequences obtained from GenBank through a pipeline consisting of masking, clustering, alignment and variation analysis steps. The STACK project aims to generate a comprehensive representation of the sequence of each of the expressed genes in the human genome by extensive processing of gene fragments to make accurate alignments, highlight diversity and provide a carefully joined set of consensus sequences for each gene. The STACK project is comprised of the STACKdb human gene index, a database of virtual human transcripts, as well as stackPACK, the tools used to create the database. STACKdb is organized into 15 tissue-based categories and one disease category. STACK is a tool for detection and visualization of expressed transcript variation in the context of developmental and pathological states. The data system organizes and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index

Proper citation: Sequence Tag Alignment and Consensus Knowledgebase Database (RRID:SCR_002156) Copy   

•   Source: SciCrunch Registry

http://www.ibiblio.org/dnam/mainpage.html

This site provides access to mutation databases and software including the human hprt database, Human p53 database, Transgenic lacZ database, and Transgenic lacI database. Other avaialble programs include Mutational spectra comparison and relational database data entry. The most recent hprt database contains information on over 2,300 mutations found in vivo and in vitro in the human hprt gene and runs under Windows. The version for evaluation on this homepage has fewer mutations and is a DOS program. The database contains information on the mutagen, dose, spontaneous and induced mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, cell type, citation, and other items. In addition, information regarding the cause and effect of mutations affecting splicing is given. Routines have been developed for the analysis of single base substitutions. The p53 database contains information on nearly 5,867 mutations found in the human p53 gene. The database itself has been updated in April of 1997. The database contains information on the cancer type, loss of heterozygosity, base position, amino acid position, amino acid change, local DNA sequence,citation, and other items. Routines have been developed for the analysis of single base substitutions. The Transgenic lacZ database contains information on 405 mutations found in vivo in the transgenic lacZ gene. It has last been updated in January of 1998. It provides information on the mutagen, dose, organ, mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, citation, and other items. The Transgenic lacI database contains information on over 1700 mutations found in vivo in the transgenic lacI gene and on nearly 8000 mutations in the lacI gene in native E. coli. The database was updated in January 1998. The database contains information on the mutagen, dose, organ, mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, citation, and other items. Routines have been developed for the analysis of single base substitutions for each of the databases. The software runs only on IBM-compatible PCs.

Proper citation: Neal's DNA Mutation Site (RRID:SCR_002947) Copy   

•   Source: SciCrunch Registry

http://www.patika.org/

The human pathway database which contains different biological entities and reactions and software tools for analysis. PATIKA Database integrates data from several sources, including Entrez Gene, UniProt, PubChem, GO, IntAct, HPRD, and Reactome. Users can query and access this data using the PATIKAweb query interface. Users can also save their results in XML or export to common picture formats. The BioPAX and SBML exporters can be used as part of this Web service.

Proper citation: Pathway Analysis Tool for Integration and Knowledge Acquisition (RRID:SCR_002100) Copy   

•   Source: SciCrunch Registry

http://dels.nas.edu/ilar

The mission of ILAR is to evaluate and disseminate information on issues related to the scientific, technological, and ethical use of animals and related biological resources in research, testing, and education. Using the principles of refinement, reduction, and replacement (3Rs) as a foundation, ILAR promotes high-quality science through the humane care and use of animals and the implementation of alternatives. Through the reports of expert committees, the ILAR Journal, web-based resources, and other means of communication, ILAR functions as a component of the National Academies to provide independent, objective advice to the federal government, the international biomedical research community, and the public. ILAR supports the responsible use of animals in research, testing, and education as a key component to advancing the health and quality of life of humans and animals. It promotes high-quality science and humane care and use of research animals based upon the principles of refinement, replacement, and reduction (the 3Rs) and high ethical standards. It fosters best practices that enhance human and animal welfare by organizing and disseminating information and by facilitating dialogue among interested parties. It has developed a unique Search Engine to search for animal models and strains. This search engine surveys all the websites of vendors and repositories of laboratory animals and biological material on our Links page. The ILAR develops guidelines on laboratory animal care and use and conducts conferences, symposia, and workshops on important laboratory animal problems. ILAR publishes the ILAR Journal on a quarterly basis, as well as conference proceedings and special reports prepared by committees of experts. A list of ILAR publications on issues related to laboratory animal research is available on the Web site. As part of the Animal Models and Genetic Stocks Information Exchange Program, ILAR staff members answer direct telephone and mail inquiries and maintain a Web page containing a database on animal models and genetic stock. The Web site also offers a comprehensive search engine that enables users to find information on the existence and location of special animal models, correct nomenclature to identify animals, and related topics such as diseases of animals and relevant publications. Sponsors: ILAR receives funding from the following sponsors: -Abbott Laboratories -Abbott Fund -American College of Laboratory Animal Medicine (ACLAM) -American Society of Laboratory Animal Practitioners (ASLAP) -Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) -Bristol-Myers Squibb Co. -Charles River -Charles River Laboratories Foundation -Covance -Federation of American Societies for Experimental Biology (FASEB) -GlaxoSmithKline -Merck & Co., Inc. -National Science Foundation (NSF) -Pfizer -Scientists Center for Animal Welfare (SCAW) -U.S. Department of Agriculture (USDA) -U.S. Department of the Army -U.S. Department of Health and Human Services (DHHS) :*National Institutes of Health (NIH) :*Office of Research Integrity (ORI) -U.S. Department of the Navy -U.S. Department of Veterans Affairs -Wellcome Trust -Wyeth Pharmaceuticals

Proper citation: Institute for Laboratory Animal Research (RRID:SCR_006872) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/news/media/audio/index.shtml

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Audio and video available from the National Institute of Mental Health (NIMH).

Proper citation: NIMH Multimedia (RRID:SCR_005467) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/

Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.

Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy   

•   Source: SciCrunch Registry

http://harvester.fzk.de/harvester/

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy   

•   Source: SciCrunch Registry

https://www.amazon.com/How-Brain-Works-Mark-Dubin/dp/0632044411

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Is the Brain (Like) a Computer is an e-book written by Prof. Mark Dubin. It consists of the following: Introduction. Why do we consider the relationship of brains and computers and what does this have to do with consciousness? What's a Brain Made Of? A thought experiment. Test Drive a Turing Machine. A theoretical approach. Interim Summary. Many of the main pages have links to additional information. When you click on one of those links a NEW page will open ON TOP of the page you are clicking from. This convention is adopted so that you can look at the additional information and then easily return to the main page you got there from.

Proper citation: Is the Brain (Like) a Computer (RRID:SCR_008809) Copy   

•   Source: SciCrunch Registry

https://nidagenetics.org/

Site for collection and distribution of clinical data related to genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis, DNA samples and cell line cultures, and data derived from genotyping and other genetic analyses of these clinical data and biomaterials, are distributed to qualified researchers studying genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to general public on release dates through distribution mechanisms specified on website.

Proper citation: National Institute on Drug Abuse Center for Genetic Studies (RRID:SCR_013061) Copy   

•   Source: SciCrunch Registry

http://rarediseases.info.nih.gov/GARD/Default.aspx

Genetic and Rare Diseases Information Center (GARD) is a collaborative effort of two agencies of the National Institutes of Health, The Office of Rare Diseases Research (ORDR) and the National Human Genome Research Institute (NHGRI) to help people find useful information about genetic conditions and rare diseases. GARD provides timely access to experienced information specialists who can furnish current and accurate information about genetic and rare diseases. So far, GARD has responded to 27,635 inquiries on about 7,147 rare and genetic diseases. Requests come not only from patients and their families, but also from physicians, nurses and other health-care professionals. GARD also has proved useful to genetic counselors, occupational and physical therapists, social workers, and teachers who work with people with a genetic or rare disease. Even scientists who are studying a genetic or rare disease and who need information for their research have contacted GARD, as have people who are taking part in a clinical study. Community leaders looking to help people find resources for those with genetic or rare diseases and advocacy groups who want up-to-date disease information for their members have contacted GARD. And members of the media who are writing stories about genetic or rare diseases have found the information GARD has on hand useful, accurate and complete. GARD has information on: :- What is known about a genetic or rare disease. :- What research studies are being conducted. :- What genetic testing and genetic services are available. :- Which advocacy groups to contact for a specific genetic or rare disease. :- What has been written recently about a genetic or rare disease in medical journals. GARD information specialists get their information from: :- NIH resources. :- Medical textbooks. :- Journal articles. :- Web sites. :- Advocacy groups, and their literature and services. :- Medical databases.

Proper citation: Genetic and Rare Diseases Information Center (RRID:SCR_008695) Copy   

•   Source: SciCrunch Registry

http://ccg.vital-it.ch/snp2tfbs

Collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. Used to investigate the molecular mechanisms underlying regulatory variation in the human genome. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs.

Proper citation: SNP2TFBS (RRID:SCR_016885) Copy   

•   Source: SciCrunch Registry

https://omicc.niaid.nih.gov

Community based, biologist friendly web platform for creating and meta analyzing annotated gene expression data compendia.

Proper citation: OMiCC (RRID:SCR_016604) Copy   

•   Source: SciCrunch Registry

http://dunham.gs.washington.edu/protocols.shtml

A portal for Maitreya Dunham's lab, which works on the genomic analysis of experimental evolution in yeast using microarrays and the chemostat. Research interests of the lab include experimental evolution of genetic networks in yeast, aneuploidy and copy number variation, comparative genomics, technology development and human genetics in yeast.

Proper citation: Maitreya Dunham's Lab (RRID:SCR_000784) Copy   

•   Source: SciCrunch Registry

http://biosciencedbc.jp/

The National Bioscience Database Center (NBDC) intends to integrate all databases for life sciences in Japan, by linking each database with expediency to maximize convenience and make the entire system more user-friendly. We aim to focus our attention on the needs of the users of these databases who have all too often been neglected in the past, rather than the needs of the people tasked with the creation of databases. It is important to note that we will continue to honor the independent integrity of each database that will contribute to our endeavor, as we are fully aware that each database was originally crafted for specific purposes and divergent goals. Services: * Database Catalog - A catalog of life science related databases constructed in Japan that are also available in English. Information such as URL, status of the database site (active vs. inactive), database provider, type of data and subjects of the study are contained for each database record. * Life Science Database Cross Search - A service for simultaneous searching across scattered life-science databases, ranging from molecular data to patents and literature. * Life Science Database Archive - maintains and stores the datasets generated by life scientists in Japan in a long-term and stable state as national public goods. The Archive makes it easier for many people to search datasets by metadata in a unified format, and to access and download the datasets with clear terms of use. * Taxonomy Icon - A collection of icons (illustrations) of biological species that is free to use and distribute. There are more than 200 icons of various species including Bacteria, Fungi, Protista, Plantae and Animalia. * GenLibi (Gene Linker to bibliography) - an integrated database of human, mouse and rat genes that includes automatically integrated gene, protein, polymorphism, pathway, phenotype, ortholog/protein sequence information, and manually curated gene function and gene-related or co-occurred Disease/Phenotype and bibliography information. * Allie - A search service for abbreviations and long forms utilized in life sciences. It provides a solution to the issue that many abbreviations are used in the literature, and polysemous or synonymous abbreviations appear frequently, making it difficult to read and understand scientific papers that are not relevant to the reader's expertise. * inMeXes - A search service for English expressions (multiple words) that appear no less than 10 times in PubMed/MEDLINE titles or abstracts. In addition, you can easily access the sentences where the expression was used or other related information by clicking one of the search results. * HOWDY - (Human Organized Whole genome Database) is a database system for retrieving human genome information from 14 public databases by using official symbols and aliases. The information is daily updated by extracting data automatically from the genetic databases and shown with all data having the identifiers in common and linking to one another. * MDeR (the MetaData Element Repository in life sciences) - a web-based tool designed to let you search, compare and view Data Elements. MDeR is based on the ISO/IEC 11179 Part3 (Registry metamodel and basic attributes). * Human Genome Variation Database - A database for accumulating all kinds of human genome variations detected by various experimental techniques. * MEDALS - A portal site that provides information about databases, analysis tools, and the relevant projects, that were conducted with the financial support from the Ministry of Economy, Trade and Industry of Japan.

Proper citation: NBDC - National Bioscience Database Center (RRID:SCR_000814) Copy   

•   Source: SciCrunch Registry

http://www.cnbc.cmu.edu/

CNBC is joint venture of University of Pittsburgh and Carnegie Mellon University. Our center leverages the strengths of the University of Pittsburgh in basic and clinical neuroscience and those of Carnegie Mellon in cognitive and computational neuroscience to support a coordinated cross-university research and educational program of international stature. In addition to our Ph.D. program in Neural Computation, we sponsor a graduate certificate program in cooperation with a wide variety of affiliated Ph.D. programs.

Proper citation: Center for the Neural Basis of Cognition (RRID:SCR_002301) Copy   

•   Source: SciCrunch Registry