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http://www.icn.ucl.ac.uk/motorcontrol/

Using robotic devices to investigate human motor behavior, this group develops computational models to understand the underlying control and learning processes. By simulating novel objects or dynamic environments they study how the brain recalibrates well-learned motor skills or acquires new ones. These insights are used to design fMRI studies to investigate how these processes map onto the brain. They have developed a number of novel techniques of how to study motor control in the MRI environment, and how to analyze MRI data of the human cerebellum. They also study patients with stroke or neurological disease to further determine how the brain manages to control the body.

Proper citation: UCL Motor Control Group (RRID:SCR_005271) Copy   

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http://europepmc.org/

Free access to biomedical literature resources including all of PubMed and PubMed Central, agricultural abstracts (from AGRICOLA), over 4 million international life science patents abstracts, National Health Service (NHS) clinical guidelines, and is supplemented with Chinese Biological Abstracts and the Citeseer database. As well as powerful search of abstracts and full text articles, it also includes: * article citations and sort order based on citation count * data citations mined from full text articles * links to and from related databases and institutional repositories * a tool to create bibliographies linked to your ORCID * named entity recognition of keywords and text-mining-based applications showcased in Europe PMC Labs * Tools for recipients of grants from one of the Europe PMC funders to deposit full-text manuscripts and link them to those specific grants. * Web services for programmatic access to all the above bibliographic information and 50,000 grants. * Search by publication date, relevance, or the number of times an article has been cited. * Links to public databases such as UniProt, Protein Data Bank (PDBe), and the European Nucleotide Archive (ENA) are provided. * Through textmining technologies, you can highlight and browse keywords such as gene names, organisms and diseases. * Search 40,000 biomedical research grants awarded to the 18,000 PIs supported by the Europe PMC funders. * Roadtest new tools based on Europe PMC content in Europe PMC labs. * In Europe PMC plus, PIs supported by the Europe PMC funders can link grants to publication information, view article citation and download statistics, and submit manuscripts.

Proper citation: Europe PubMed Central (RRID:SCR_005901) Copy   

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http://eupathdb.org/eupathdb/

EuPathDB integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises veterinary and medically important parasitic protozoa including human pathogenic species of genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as database but unifies access to three major existing individual organism databases, PlasmoDB.org, ToxoDB.org and CryptoDB.org, and integrates these databases with data available from additional sources. Through ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases. EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with eukaryotic pathogens.

Proper citation: Eukaryotic Pathogen Database Resources (RRID:SCR_004512) Copy   

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http://www.genedb.org/Homepage/Lmajor

Database of the most recent sequence updates and annotations for the L. major genome. New annotations are constantly being added to keep up with published manuscripts and feedback from the Trypanosomatid research community. You may search by Protein Length, Molecular Mass, Gene Type, Date, Location, Protein Targeting, Transmembrane Helices, Product, GO, EC, Pfam ID, Curation and Comments, and Dbxrefs. BLAST and other tools are available. Leishmania species cause a spectrum of human diseases in tropical and subtropical regions of the world. We have sequenced the 36 chromosomes of the 32.8-megabase haploid genome of Leishmania major (Friedlin strain) and predict 911 RNA genes, 39 pseudogenes, and 8272 protein-coding genes, of which 36% can be ascribed a putative function. These include genes involved in host-pathogen interactions, such as proteolytic enzymes, and extensive machinery for synthesis of complex surface glycoconjugates. The Pathogen Genomics group at the Wellcome Trust Sanger Institute played a major role in sequencing the genome of Leishmania major (see Ivens et al.) Details of the centres involved and which chromosomes they sequenced, are given. The sequence data were obtained by adopting several parallel approaches, including complete cosmid sequencing, whole chromosome shotguns and/or BAC sequencing/skimming. The Leishmania parasite is an intracellular pathogen of the immune system targeting macrophages and dendritic cells. The disease Leishmaniasis affects the populations of 88 counties worldwide with symptoms ranging from disfiguring cutaneous and muco-cutaneous lesions that can cause widespread destruction of mucous membranes to visceral disease affecting the haemopoetic organs. In collaboration with GeneDB, the EuPathDB genomic sequence data and annotations are regularly deposited on TriTrypDB where they can be integrated with other datasets and queried using customized queries.

Proper citation: GeneDB Lmajor (RRID:SCR_004613) Copy   

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http://treestoolbox.org/

Software package, written in Matlab (Mathworks, Natick, MA), providing tools to automatically reconstruct neuronal branching from microscopy image stacks and to generate synthetic axonal and dendritic trees. It provides the basic tools to edit, visualize and analyze dendritic and axonal trees, methods for quantitatively comparing branching structures between neurons, and tools for exploring how dendritic and axonal branching depends on local optimization of total wiring and conduction distance.

Proper citation: TREES toolbox (RRID:SCR_010457) Copy   

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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

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   

•   Source: SciCrunch Registry

http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://www.openmicroscopy.org/site/support/ome-model/ome-tiff/

A standardized file format for multidimensional microscopy image data. OME-TIFF maximizes the respective strengths of OME-XML and TIFF. It takes advantage of the rich metadata defined in OME-XML while retaining the pixel structure in multi-page TIF format for compatibility with many image-processing applications. An OME-TIFF dataset has the following characteristics: * Image planes are stored within one multi-page TIFF file, or across multiple TIFF files. Any image organization is feasible. * A complete OME-XML metadata block describing the dataset is embedded in each TIFF file's header. Thus, even if some of the TIFF files in a dataset are misplaced, the metadata remains intact. * The OME-XML metadata block may contain anything allowed in a standard OME-XML file. * OME-TIFF uses the standard TIFF mechanism for storing one or more image planes in each of the constituent files, instead of encoding pixels as base64 chunks within the XML. Since TIFF is an image format, it makes sense to only use OME-TIFF as opposed to OME-XML, when there is at least one image plane.

Proper citation: OME-TIFF Format (RRID:SCR_002636) Copy   

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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   

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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   

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http://genomics.senescence.info/diet/

Database of genes associated with dietary restriction. It includes genes inferred from experiments in model organisms in which genetic manipulations cancel out or disrupt the life-extending effects of dietary restriction and genes robustly altered due to dietary restriction, derived from a meta-analysis of microarray studies in mammals.

Proper citation: Dietary Restriction Gene Database (RRID:SCR_013720) Copy   

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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   

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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   

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http://www.ebi.ac.uk/goldman-srv/pandit

PANDIT is a collection of multiple sequence alignments and phylogenetic trees covering many common protein domains. It contains: * the seed protein sequence alignments from the Pfam-A (curated families) database (version 17.0) * nucleotide sequence alignments derived from sequences available for the above and using the protein alignments as "templates"; * protein sequence alignments restricted to the family members for which nucleotide sequences are available * inferred phylogenetic trees for each alignment The data in PANDIT and the dataset's development have been frozen owing to a lack of funding support. The existing data, version 17.0 corresponding to Pfam 17.0, remain stable and, we hope, useful. The entire database is also available for download as a flatfile from this website.

Proper citation: PANDIT : Protein and Associated Nucleotide Domains with Inferred Trees (RRID:SCR_003321) Copy   

•   Source: SciCrunch Registry

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

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   

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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