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https://github.com/Core-Bioinformatics/bulkAnalyseR

Software R package for most bulk sequencing datasets. Creates shiny app for interactive data analysis and visualisation. Used for analysing and sharing bulk sequencing results.

Proper citation: bulkAnalyseR (RRID:SCR_027647) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/

Non profit research organization for genome sequences to advance understanding of biology of humans and pathogens in order to improve human health globally. Provides data which can be translated for diagnostics, treatments or therapies including over 100 finished genomes, which can be downloaded. Data are publicly available on limited basis, and provided more extensively upon request.

Proper citation: Wellcome Trust Sanger Institute; Hinxton; United Kingdom (RRID:SCR_011784) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/NeuroimagingMetaAnalysis/ibma

Image-Based Meta-Analysis toolbox for SPM. Implementation of z-based statistics: Fisher's, Stouffer's.

Proper citation: IBMA toolbox (RRID:SCR_003772) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/artemis/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Free genome browser and annotation tool that allows visualization of sequence features, next generation data and the results of analyses within the context of the sequence, and also its six-frame translation. Artemis is free software and is distributed under the terms of the GNU General Public License. Artemis is written in Java, and is available for UNIX, Macintosh and Windows systems. It can read EMBL and GENBANK database entries or sequence in FASTA, indexed FASTA or raw format. Other sequence features can be in EMBL, GENBANK or GFF format.

Proper citation: Artemis: Genome Browser and Annotation Tool (RRID:SCR_004267) Copy   

•   Source: SciCrunch Registry

https://ibeximagingcommunity.github.io/ibex_imaging_knowledge_base/

Open, global repository as central resource for reagents, protocols, panels, publications, software, and datasets. In addition to IBEX, we support standard, single cycle multiplexed imaging (Multiplexed 2D imaging), volume imaging of cleared tissues with clearing enhanced 3D (Ce3D), highly multiplexed 3D imaging (Ce3D-IBEX), and extension of the IBEX dye inactivation protocol to the Leica Cell DIVE (Cell DIVE-IBEX). Committed to sharing knowledge related to multiplexed imaging. Antibody validation community knowledgebase.

Proper citation: IBEX Knowledge Base (RRID:SCR_025296) 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.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   

•   Source: SciCrunch Registry

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://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   

•   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

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   

•   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://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

http://mus.well.ox.ac.uk/mouse/INBREDS/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.

Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy   

•   Source: SciCrunch Registry

http://www.africacentre.ac.za/Default.aspx?tabid=69

Longitudinal datasets of demographic, social, medical and economic information from a rural demographic in northern KwaZulu-Natal, South Africa where HIV prevalence is extremely high. The data may be filtered by demographics, years, or by individuals questionnaires. The datasets may be used by other researchers but the Africa Centre requests notification that anyone contact them when downloading their data. The datasets are provided in three formats: Stata11 .dta; tables in a MS-Access .accdb database; and worksheets in a MS-Excel .xlsx workbook. Datasets are generated approximately every six months containing information spanning the whole period of surveillance from 1/1/2000 to present.

Proper citation: Africa Centre for Health and Population Studies (RRID:SCR_008964) 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