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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://genomics.senescence.info/
Collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses. A major resource in HAGR is GenAge, which includes a curated database of genes related to human aging and a database of ageing- and longevity-associated genes in model organisms. Another major database in HAGR is AnAge. Featuring over 4,000 species, AnAge provides a compilation of data on aging, longevity, and life history that is ideal for the comparative biology of aging. GenDR is a database of genes associated with dietary restriction based on genetic manipulation experiments and gene expression profiling. Other projects include evolutionary studies, genome sequencing, cancer genomics, and gene expression analyses. The latter allowed them to identify a set of genes commonly altered during mammalian aging which represents a conserved molecular signature of aging. Software, namely in the form of scripts for Perl and SPSS, is made available for users to perform a variety of bioinformatic analyses potentially relevant for studying aging. The Perl toolkit, entitled the Ageing Research Computational Tools (ARCT), provides modules for parsing files, data-mining, searching and downloading data from the Internet, etc. Also available is an SPSS script that can be used to determine the demographic rate of aging for a given population. An extensive list of links regarding computational biology, genomics, gerontology, and comparative biology is also available.
Proper citation: Human Ageing Genomic Resources (RRID:SCR_007700) Copy
Repository of biological models created using CellML, a free, open-source, eXtensible markup language based standard for defining mathematical models of cellular function. Models may be browsed by category, which include: Calcium Dynamics, Cardiovascular Circulation, Cell Cycle, Cell Migration, Circadian Rhythms, Electrophysiology, Endocrine, Excitation-Contraction Coupling, Gene Regulation, Hepatology, Immunology, Ion Transport, Mechanical Constitutive Laws, Metabolism, Myofilament Mechanics, Neurobiology, pH Regulation, PKPD, Signal Transduction, Synthetic Biology. The community can contribute their models to this resource.
Proper citation: CellML Model Repository (RRID:SCR_008113) Copy
The CellML language is an open standard based on the XML markup language. The purpose of CellML is to store and exchange computer-based mathematical models. CellML allows scientists to share models even if they are using different model-building software. It also enables them to reuse components from one model in another, thus accelerating model building. Although CellML was originally intended for the description of biological models; CellML includes information about model structure (how the parts of a model are organizationally related to one another), mathematics (equations describing the underlying processes) and metadata (additional information about the model that allows scientists to search for specific models or model components in a database or other repository). The CellML team is committed to providing freely available tools for creating, editing, and using CellML models. We provide information regarding tools we are developing internally and links to external projects developing tools which utilize the CellML format. Please let us know if you have an open source CellML tool looking for a home on the internet, as we are able to offer limited hosting services on cellml.org.
Proper citation: CellML (RRID:SCR_008061) Copy
Non-profit organization dedicated to solving the author/contributor name ambiguity problem in scholarly communications by creating a central registry of unique identifiers for individual researchers and an open and transparent linking mechanism between ORCID and other current author ID schemes. These identifiers, and the relationships among them, can be linked to the researcher''s output to enhance the scientific discovery process and to improve the efficiency of research funding and collaboration within the research community. The ideal solution is to establish a registry that is adopted and embraced as the de facto standard by the whole of the community. A resolution to the systemic name ambiguity problem, by means of assigning unique identifiers linkable to an individual''s research output, will enhance the scientific discovery process and improve the efficiency of funding and collaboration. The organization brings together the leaders of the most influential universities, funding organizations, societies, publishers and corporations from around the globe and is managed by a fourteen member Board of Directors. A disambiguated set of authors will allow new services and benefits to be built for the research community by all stakeholders in scholarly communication: from commercial actors to non-profit organizations, from governments to universities.
Proper citation: ORCID - Open Researcher and Contributor ID (RRID:SCR_008700) Copy
http://www.evocontology.org/site/Main/EvocOntologyDotOrg
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., documented September 6, 2016. Set of orthogonal controlled vocabularies that unifies gene expression data by facilitating a link between the genome sequence and expression phenotype information. The system associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. The four core eVOC ontologies provide an appropriate set of detailed human terms that describe the sample source of human experimental material such as cDNA and SAGE libraries. These expression terms are linked to libraries and transcripts allowing the assessment of tissue expression profiles, differential gene expression levels and the physical distribution of expression across the genome. Analysis is currently possible using EST and SAGE data, with microarray data being incorporated. The eVOC data is increasingly being accepted as a standard for describing gene expression and eVOC ontologies are integrated with the Ensembl EnsMart database, the Alternate Transcript Diversity Project and the UniProt Knowledgebase. Several groups are currently working to provide shared development of this resource such that it is of maximum use in unifying transcript expression information.
Proper citation: eVOC (RRID:SCR_010704) Copy
http://www.biomart.org/biomart/martview/ddb9ce1ad275cde372c968d13fa11f5f
A web server interface of BioMart software and provides a unified view over disparate data sources that enable bioscientists to retrieve data from one or multiple sources in a simple and efficient way. This MartView web server features seamless data federation making cross querying of data sources in a user friendly and unified way. Data sources include major biomolecular sequence, pathway and annotation databases such as Ensembl, Uniprot, Reactome, HGNC, Wormbase, etc. The web server not only provides access through a web interface, it also supports programmatic access through a Perl API as well as RESTful and SOAP oriented web services.
Proper citation: BioMart MartView (RRID:SCR_010714) Copy
http://www.guidetopharmacology.org
Portal and searchable database of pharmacological information. Information is presented at two levels, the initial view or landing pages for each target family provide expert-curated overviews of the key properties and the available selective ligands and tool compounds. For selected targets, more detailed introductory chapters for each family are available along with curated information on the pharmacological, physiological, structural, genetic and pathophysiogical properties of each target.
Proper citation: IUPHAR/BPS Guide to Pharmacology (RRID:SCR_013077) Copy
https://github.com/sanger-pathogens/ariba
Analysis software that identifies antibiotic resistance genes by running local assemblies. It can also be used for MLST calling.
Proper citation: Ariba (RRID:SCR_015976) Copy
http://www.functionalnet.org/humannet/about.html
Database of human protein-encoding genes that is constructed by a modified Bayesian integration of 'omics' data from multiple organisms. Each data type is weighted according to how well it links genes that are known to function together in humans, and each interaction has an associated log-likelihood score (LLS) that measures the probability of an interaction representing a true functional linkage between two genes.
Proper citation: HumanNet (RRID:SCR_016146) Copy
https://github.com/HicServices/RDMP/wiki
Software toolkit which automates the loading, storage, linkage and provision of data sets. It also cleans, transforms and documents provenance meta-data and domain knowledge to make data sets “research ready”.
Proper citation: Research Data Management Platform (RRID:SCR_016268) Copy
https://github.com/linnarsson-lab/cytograph
Software multistage analysis pipeline which progressively discovers cell types or states while mitigating impact of technical artifacts.Used for single cell analysis.
Proper citation: Cytograph (RRID:SCR_023101) Copy
Web application as repository and launch platform for Psychopy experiments and other open-source tools.
Proper citation: Pavlovia (RRID:SCR_023320) Copy
http://www.genes2cognition.org/db/Search
Database of protein complexes, protocols, mouse lines, and other research products generated from the Genes to Cognition project, a project focused on understanding molecular complexes involved in synaptic transmission in the brain.
Proper citation: Genes to Cognition Database (RRID:SCR_002735) Copy
Ratings or validation data are available for this resource
Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.
Proper citation: GENCODE (RRID:SCR_014966) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A nucleotide sequence based approach for the unambiguous characterisation of isolates of bacteria and other organisms via the internet. The aim of MLST is to provide a portable, accurate, and highly discriminating typing system that can be used for most bacteria and some other organisms. It is envisaged that this approach will be particularly helpful for the typing of bacterial pathogens. To achieve this aim we have taken the proven concepts of multilocus enzyme electrophoresis (MLEE) and have adapted them so that alleles at each locus are defined directly, by nucleotide sequencing, rather than indirectly from the electrophoretic moblity of their gene products. MLST was developed in the laboratories of Martin Maiden, Dominique Caugant, Ian Feavers, Mark Achtman and Brian Spratt. This site is hosted at Imperial College with funding from the Wellcome Trust. The location of the subsites for the individual species are shown on their respective front pages.
Proper citation: MLST (RRID:SCR_010245) Copy
Database that contains data such as registry entries, portions of regulatory documents describing individual trials, structured data on methods and results, and researchers and papers from and/or related to clinical trials. The initiative aims to locate, match, and share all publicly accessible data and documents, on all trials conducted, on all medicines and other treatments, globally.
Proper citation: Open Trials (RRID:SCR_015570) Copy
Atlas of brain cell types, derived from single cell RNA-Seq data from Linnarsson Lab. Can be browsed by taxon, cell type, tissue, and gene, with information on enriched genes, specific markers, anatomical location and more. Single cell gene expression atlas of mouse nervous system.
Proper citation: mousebrain.org (RRID:SCR_016999) Copy
Collection of structured and manually curated data of current therapeutic interventions in aging and age-related disease. Describes compounds and mechanisms using multiple chemical and biological databases.
Proper citation: GEROprotectors (RRID:SCR_016737) Copy
https://github.com/kjolley/BIGSdb
Platform for gene-by-gene bacterial population annotation and analysis. Designed to store and analyse sequence data for bacterial isolates. Used for scalable analysis of bacterial genome variation at population level.
Proper citation: BIGSdb (RRID:SCR_023551) Copy
https://bioconductor.org/packages/release/bioc/html/PhenStat.html
Software R package for statistical analysis of phenotypic data.Tool kit for standardized analysis of high throughput phenotypic data.
Proper citation: PhenStat (RRID:SCR_021317) Copy
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