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http://old.genedb.org/genedb/glossina/

As of 12th March 2009, GeneDB provides access to the transcriptome of the Tsetse fly Glossina morsitans morsitans, the biological vector of African trypanosomiases. The current data set includes: >>7,015 contigs comprised of ESTs from Trypanosoma brucei infected midgut tissue (Lehane et al, Genome Biol. 2003;4(10):R63) >>7,493 contigs comprised of ESTs from salivary gland tissue >>18,404 contigs comprised of EST pooled from a range of different tissue- and developmental stage-specific libraries: head (2,700 ESTs), midgut (21,662 ESTs), reproductive organs (3, 438 ESTs), salivary gland (27,426 ESTs), larvae (2,304 ESTs), pupae (2,304 ESTs), fatbody (20,257 ESTs) (Attardo et al, Insect Molecular Biology 2006, 15(4):411-424), male and female whole bodies (19,968 ESTs). These data include the midgut and salivary gland ESTs used in the library specific clustering for the contig sets listed above. Initial automated annotations of product descriptions were manually revised by participants in two community annotation jamborees held under the auspice of the International Glossina Genome Initiative (IGGI) with funding by TDR. A Glossina morsitans morsitans genome project is currently also underway. To date, 2.4M capillary shotgun reads have been produced and the initial assembly is available to download via the ftp server and for blast analysis.

Proper citation: GeneDB Gmorsitans (RRID:SCR_004310) 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

http://zebrafishucl.org/zebrafishbrain#about-1

Collates and curates neuroanatomical data and information generated both in-house and by community to communicate current state of knowledge about neuroanatomical structures in developing zebrafish. Most of data come from high resolution confocal imaging of intact brains in which neuroanatomical structures are labelled by combinations of transgenes and antibodies. Community repository for image based data related to neuroanatomy of zebrafish.

Proper citation: Zebrafish Brain Atlas (RRID:SCR_000606) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/resources/

Biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline as part of the Genes to Cognition research program are freely-available to interested researchers. Available Transgenic Mouse Lines: *Hras1 (H-ras) knockout,C57BL/6J *Dlg4 (PSD-95) knockout,129S5 *Dlg4 (PSD-95) knockout,C57BL/6J *Dlg3 (SAP102) knockout with hprt mutation,129S5 *Dlg3 (SAP102) knockout (wild-type for hprt,C57BL/6J *Syngap1 (SynGAP) knockout (from 8.24 clone), C57BL/6J *Dlg4 (PSD-95) guanylate kinase domain deletion, C57BL/6J *Ptk2 (FAK) knockout,C57BL/6J

Proper citation: Genes to Cognition - Biological Resources (RRID:SCR_001675) Copy   

•   Source: SciCrunch Registry

http://tritrypdb.org/tritrypdb/

An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).

Proper citation: TriTrypDB (RRID:SCR_007043) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/enzymes/

Database of known enzyme structures that have been deposited in the Protein Data Bank (PDB). The enzyme structures are classified by their E.C. number of the ENZYME Data Bank. Browse the classification hierarchy or enter an EC number or search-string. There are currently 45,638 PDB-enzyme entries in the PDB (as at 23 February, 2013) involving 38,109 separate PDB files - some files having more than one E.C. number associated with them.

Proper citation: Enzyme Structures Database (RRID:SCR_007125) Copy   

•   Source: SciCrunch Registry

http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

•   Source: SciCrunch Registry

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

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

Ratings or validation data are available for this resource

https://www.gencodegenes.org

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   

•   Source: SciCrunch Registry

https://github.com/JCVenterInstitute/NSForest/releases

Software tool as method that takes cluster results from single cell nuclei RNAseq experiments and generates lists of minimal markers needed to define each cell type cluster. Utilizes random forest of decision trees machine learning approach. Used to determine minimum set of marker genes whose combined expression identified cells of given type with maximum classification accuracy.

Proper citation: NS-Forest (RRID:SCR_018348) Copy   

•   Source: SciCrunch Registry

https://sanger-pathogens.github.io/Roary/

Software tool for rapid large scale prokaryote pan genome analysis. Builds large scale pan genomes, identifying core and accessory genes. Makes construction of pan genome of thousands of prokaryote samples on standard desktop without compromising on accuracy of results. Not intended for meta genomics or for comparing extremely diverse sets of genomes.

Proper citation: Roary (RRID:SCR_018172) Copy   

•   Source: SciCrunch Registry

https://github.com/xavierdidelot/clonalorigin

Software package for comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.

Proper citation: ClonalOrigin (RRID:SCR_016061) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://pavlovia.org/

Web application as repository and launch platform for Psychopy experiments and other open-source tools.

Proper citation: Pavlovia (RRID:SCR_023320) Copy   

•   Source: SciCrunch Registry

https://github.com/MetaCell/nwb-explorer

Web application and standalone application to read, visualize and explore content of NWB:N 2 files.Used to share neurophysiological data in Neurodata Without Borders format.

Proper citation: NWB Explorer (RRID:SCR_021151) Copy   

•   Source: SciCrunch Registry

https://spikeinterface.readthedocs.io

Software tool as unified framework for spike sorting. Python framework to unify preexisting spike sorting technologies into single codebase and to facilitate straightforward comparison and adoption of different approaches.Used to reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs.

Proper citation: SpikeInterface (RRID:SCR_021150) Copy   

•   Source: SciCrunch Registry