Tools   Select Another Resource Report Type

https://www.openmicroscopy.org/site/products/bio-formats

Standalone software Java library for reading microscopy image data files in any format and writing image data using standardized, open formats. It currently reads and converts more than 120 file formats to the OME-TIFF data standard.

Proper citation: Bio-Formats (RRID:SCR_000450) 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://flybrain.stanford.edu/

Project content including raw image data, neuronal tracings, image registration tools and analysis scripts covering three manuscripts: Comprehensive Maps of DrosophilaHigher Olfactory Centres : Spatially Segregated Fruit and Pheromone Representation which uses single cell labeling and image registration to describe the organization of the higher olfactory centers of Drosophila; Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe which uses single cell labeling to describe the organization of the antennal lobe local interneurons; and Sexual Dimorphism in the Fly Brain which uses clonal analysis and image registration to identify a large number of sex differences in the brain and VNC of Drosophila. Data * Raw Data of Reference Brain (pic, amira) (both seed and average) * Label field of LH and MB calyx and surfaces for these structures * Label field of neuropil of Reference Brain * Traces (before and after registration). Neurolucida, SWC and AmiraMesh lineset. * MB and LH Density Data for different classes of neuron. In R format and as separate amira files. * Registration files for all brains used in the study * MBLH confocal images for all brains actually used in the study (Biorad pic format) * Sample confocal images for antennal lobe of every PN class * Confocal stacks of GABA stained ventral PNs Programs * ImageJ plugins (Biorad reader /writer/Amira reader/writer/IGS raw Reader) * Binary of registration, warp and gregxform (macosx only, others on request) * Simple GUI for registration tools (macosx only at present) * R analysis/visualization functions * Amira Script to show examples of neuronal classes The website is a collaboration between the labs of Greg Jefferis and Liqun Luo and has been built by Chris Potter and Greg Jefferis. The core Image Registration tools were created by Torsten Rohlfing and Calvin Maurer.

Proper citation: Flybrain at Stanford (RRID:SCR_001877) 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

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

http://www.orcid.org/

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   

•   Source: SciCrunch Registry

http://tree.bio.ed.ac.uk/software/seqgen/

Software program that simulates the evolution of nucleotide or amino acid sequences along a phylogeny using common models of the substitution process. A range of models of molecular evolution are implemented, including the general reversible model. State frequencies and other parameters of the model may be given and site-specific rate heterogeneity may also be incorporated in a number of ways. Any number of trees may be read in and the program will produce any number of data sets for each tree.

Proper citation: Seq-Gen (RRID:SCR_014934) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/robince/gcmi

Software package of functions for calculating mutual information and other information theoretic quantities using a parametric Gaussian copula.

Proper citation: Gaussian-Copula Mutual Information (GCMI) (RRID:SCR_016450) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM

Software tool for inference using permutation methods. Requires Matlab or Octave. Can be executed from inside either environment, or directly from the shell and can be called from scripts. For users who are familiar with statistics and willing to use experimental analysis tools.

Proper citation: PALM (RRID:SCR_017029) Copy   

•   Source: SciCrunch Registry

https://models.physiomeproject.org

Repository of mainly CellML models powered by collection of software tools and libraries with PMR2 software suite as core power. Third party integration suites are RICORDO, Virtuoso, BiVeS/BudHat, OpenCOR, CombineArchive Web, WebCAT, Morre/MaSyMoS.

Proper citation: Physiome Model Repository (RRID:SCR_017374) Copy   

•   Source: SciCrunch Registry

http://www.vasotracker.com

Open source and stand alone software for assessing vascular reactivity. Used in pressure myograph system.

Proper citation: VasoTracker (RRID:SCR_017233) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry