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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   

•   Source: SciCrunch Registry

http://www.cellml.org/models

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   

•   Source: SciCrunch Registry

http://www.cellml.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/alexlib/KymoButler-1

Software tool as deep learning software for automated kymograph analysis. Uses artificial intelligence to trace lines in kymograph and extract information about particle movement. Speeds up analysis of kymographs by between 50 and 250 times, and comparisons show that it is as reliable as manual analysis.

Proper citation: KymoButler (RRID:SCR_021717) Copy   

•   Source: SciCrunch Registry

https://shiny.cnsgenomics.com/mRnd/

Web tool for calculations for Mendelian Randomization. Power calculations for Mendelian Randomization. Used to calculate statistical power for Mendelian Randomization study, using Non Centrality Parameter based approach.

Proper citation: mRnd (RRID:SCR_022156) Copy   

•   Source: SciCrunch Registry

http://www.biomart.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4,2023.Platform provides free software and data services to international scientific community in order to foster scientific collaboration and facilitate scientific discovery process. Project adheres to open source philosophy that promotes collaboration and code reuse.

Proper citation: BioMart Project (RRID:SCR_002987) Copy   

•   Source: SciCrunch Registry

http://merops.sanger.ac.uk/

An information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.

Proper citation: MEROPS (RRID:SCR_007777) Copy   

•   Source: SciCrunch Registry

http://supfam.mbu.iisc.ernet.in/index.html

SUPFAM is a database that consists of clusters of potentially related homologous protein domain families, with and without three-dimensional structural information, forming superfamilies. The present release (Release 3.0) of SUPFAM uses homologous families in Pfam (Version 23.0) and SCOP (Release 1.69) which are examples of sequence -alignment and structure classification databases respectively. The two steps involved in setting up of SUPFAM database are * Relating Pfam and SCOP families using a new profile-profile alignment algorithm AlignHUSH. This results in identifying many Pfam families which could be related to a family or superfamily of known structural information. * An all-against-all match among Pfam families with yet unknown structure resulting in identification of related Pfam families forming new potential superfamilies. The SUPFAM database can be used in either the Browse mode or Search mode. In Browse mode you can browse through the Superfamilies, Pfam families or SCOP families. In each of these modes you will be presented with a full list which can be easily browsed. In Search mode, you can search for Pfam families, SCOP families or Superfamilies based on keywords or SCOP/Pfam identifiers of families and superfamilies., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SUPFAM (RRID:SCR_005304) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/depressiondatabase/

The Major Depressive Disorder Neuroimaging Database (MaND) contains information of 225 studies which have investigated brain structure (using MRI and CT scans) in patients with major depressive disorder compared to a control group. 143 studies and 63 brain structures are included in the meta-analysis. The database and meta-analysis are contained in an Excel spreadsheet file which may be freely downloaded from this website.

Proper citation: Major depressive disorder neuroimaging database (RRID:SCR_005835) Copy   

•   Source: SciCrunch Registry

http://decipher.sanger.ac.uk/

Interactive database which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance. Used to enhance clinical diagnosis by retrieving information from bioinformatics resources relevant to the imbalance found in the patient. Contributing to the DECIPHER database is a Consortium, comprising an international community of academic departments of clinical genetics. Each center maintains control of its own patient data (which are password protected within the center''''s own DECIPHER project) until patient consent is given to allow anonymous genomic and phenotypic data to become freely viewable within Ensembl and other genome browsers. Once data are shared, consortium members are able to gain access to the patient report and contact each other to discuss patients of mutual interest, thus facilitating the delineation of new microdeletion and microduplication syndromes.

Proper citation: DECIPHER (RRID:SCR_006552) Copy   

•   Source: SciCrunch Registry

http://www.mlst.net/

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   

•   Source: SciCrunch Registry

https://opentrials.net/

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   

•   Source: SciCrunch Registry

http://mousebrain.org/

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   

•   Source: SciCrunch Registry

http://geroprotectors.org

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://data.broadinstitute.org/alkesgroup/Eagle/

Software package for statistical estimation of haplotype phase either within a genotyped cohort or using a phased reference panel in large scale sequencing. The package includes Eagle1 (to harness identity-by-descent among distant relatives to rapidly call phase using a fast scoring approach) and Eagle2 (to analyze a full probabilistic model similar to the diploid Li-Stephens model used by previous HMM-based methods.

Proper citation: Eagle (RRID:SCR_015991) Copy   

•   Source: SciCrunch Registry

https://github.com/huwjenkins/fragon

Software tool for rapid high resolution structure determination from ideal protein fragments. Pipeline to determine crystal structures using molecular replacement with small fragments followed by density modification. It is available through CCP4.

Proper citation: fragon (RRID:SCR_019158) Copy   

•   Source: SciCrunch Registry

http://www.ukbiobank.ac.uk/

Biobank provides data collected at Assessment Center and via online questionnaires on participants aged 40-69 years recruited throughout United Kingdom and provides summary information to improve prevention, diagnosis and treatment of serious and life threatening illnesses.

Proper citation: UK Biobank (RRID:SCR_012815) Copy   

•   Source: SciCrunch Registry