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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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http://www.well.ox.ac.uk/

An international leader in genetics, genomics and structural biology, and research institute of the Nuffield Department of Medicine at the University of Oxford, whose objective is to extend our understanding on how genetic inheritance makes us who we are in order to gain a clearer insight into mechanisms of health and disease. Looking across all three billion letters of the human genetic code, they aim to pinpoint variant spellings and discover how they increase or decrease an individual's risk of falling ill. They collaborate with research teams across the world on a number of large-scale studies in these areas.

Proper citation: Wellcome Trust Centre for Human Genetics (RRID:SCR_003307) Copy   


http://www.ebi.ac.uk/pride/

Centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. Originally it was developed to provide a common data exchange format and repository to support proteomics literature publications. This remit has grown with PRIDE, with the hope that PRIDE will provide a reference set of tissue-based identifications for use by the community. The future development of PRIDE has become closely linked to HUPO PSI. PRIDE encourages and welcomes direct user submissions of protein and peptide identification data to be published in peer-reviewed publications. Users may Browse public datasets, use PRIDE BioMart for custom queries, or download the data directly from the FTP site. PRIDE has been developed through a collaboration of the EMBL-EBI, Ghent University in Belgium, and the University of Manchester.

Proper citation: Proteomics Identifications (PRIDE) (RRID:SCR_003411) Copy   


http://www.roslin.ed.ac.uk/about-roslin/

The world''s largest collection of tick cell lines, enabling scientists to carry out advanced research. This biobank is establishing a collection of all the continuous cell lines derived from ixodid and argasid ticks of medical and veterinary importance available worldwide now and in future. Ticks are blood feeding arthropods which transmit many human and animal diseases. Research into prevention and cure of these diseases, which are caused by viruses, bacteria and protozoa, is greatly assisted by the use of cell culture systems which enable study of both how tick cells function, and how and why ticks transmit these disease-causing pathogens. Cell lines will always be shipped to recipient laboratories as growing cultures, since we cannot guarantee successful resuscitation of frozen stabilates. Tick cells in culture can tolerate the range of temperatures experienced during transit by air for up to a week. Training: We will provide training in tick cell line care and maintenance. This is an essential component of successful transfer of tick cells to, and their establishment in, laboratories with little or no previous experience of tick cell culture. Recipient scientists (preferably the person who will actually look after the cells) can visit the biobank for between 2 days and 2 weeks, depending on their level of previous experience, to be trained in the specific approach and methods for tick cell cultivation. Establishment of new cell lines: In response to requests and on receipt of suitable starting material (engorged female or moulting nymphal ticks), we will attempt to establish new cell lines from tick species or strains which are not already represented in the collection. Deposition of new tick cell lines: We invite researchers anywhere in the world who have established new tick cell lines to deposit samples for safekeeping free of charge and, if requested, for distribution alongside the existing biobank portfolio.

Proper citation: Roslin Wellcome Trust Tick Cell Biobank (RRID:SCR_004228) Copy   


  • RRID:SCR_004181

http://images.wellcome.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023.Digital collection of images, with themes ranging from medical and social history to contemporary healthcare and biomedical science. The collection contains historical images from the Wellcome Library collections, Tibetan Buddhist paintings, ancient Sanskrit manuscripts written on palm leaves, beautifully illuminated Persian books and much more. The Biomedical Collection holds over 40 000 high-quality images from the clinical and biomedical sciences. Selected from the UK''s leading teaching hospitals and research institutions, it covers disease, surgery, general healthcare, sciences from genetics to neuroscience including the full range of imaging techniques. They are always looking for new high quality biomedical images from scientific researchers, clinical photographers and artists in any field of science or medicine. As a contributor you retain your original material and copyright, and receive commission and full credit each time your images are used. The annual Wellcome Images awards (previously known as Biomedical Images Awards) reward contributors for their outstanding work and winners are chosen by a panel of experts. The resulting public exhibitions are always extremely popular and receive widespread acclaim. All images on the Wellcome Images site are available free for use in: * private study and non-commercial research * examination papers * criticism and review, this applies only where there are no multiple copies made * theses submitted by a student at a higher or further education institution for the purposes of securing a degree * personal use by private individuals

Proper citation: Wellcome Images (RRID:SCR_004181) Copy   


  • RRID:SCR_004786

    This resource has 10+ mentions.

http://www.genedb.org/Homepage/Tbruceibrucei927

Database of the most recent sequence updates and annotations for the T. brucei 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. T. brucei possesses a two-unit genome, a nuclear genome and a mitochondrial (kinetoplast) genome with a total estimated size of 35Mb/haploid genome. The nuclear genome is split into three classes of chromosomes according to their size on pulsed-field gel electrophoresis, 11 pairs of megabase chromosomes (0.9-5.7 Mb), intermediate (300-900 kb) and minichromosomes (50-100 kb). The T. brucei genome contains a ~0.5Mb segmental duplication affecting chromosomes 4 and 8, which is responsible for some 75 gene duplicates unique to this species. A comparative chromosome map of the duplicons can be accessed here (PubmedID 18036214). Protozoan parasites within the species Trypanosoma brucei are the etiological agent of human sleeping sickness and Nagana in animals. Infections are limited to patches of sub-Saharan Africa where insects vectors of the Glossina genus are endemic. The most recent estimates indicate between 50,000 - 70,000 human cases currently exist, with 17 000 new cases each year (WHO Factsheet, 2006). 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 Tbrucei (RRID:SCR_004786) Copy   


http://dictybase.org/Dicty_Info/dicty_anatomy_ontology.html

An ontology to describe Dictyostelium where the structural makeup of Dictyostelium and its composing parts including the different cell types, throughout its life cycle is defined. There are two main goals for this new tool: (1) promote the consistent annotation of Dictyostelium-specific events, such as phenotypes (already in use), and in the future, of gene expression information; and (2) encourage researchers to use the same terms with the same intended meaning. To this end, all terms are defined. The complete ontology can be browsed using EBI''s ontology browser tool. (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=DDANAT)

Proper citation: Dictyostelium Anatomy Ontology (RRID:SCR_005929) Copy   


  • RRID:SCR_006070

    This resource has 10+ mentions.

http://www.nematodes.org/nembase4/

NEMBASE is a comprehensive Nematode Transcriptome Database including 63 nematode species, over 600,000 ESTs and over 250,000 proteins. Nematode parasites are of major importance in human health and agriculture, and free-living species deliver essential ecosystem services. The genomics revolution has resulted in the production of many datasets of expressed sequence tags (ESTs) from a phylogenetically wide range of nematode species, but these are not easily compared. NEMBASE4 presents a single portal into extensively functionally annotated, EST-derived transcriptomes from over 60 species of nematodes, including plant and animal parasites and free-living taxa. Using the PartiGene suite of tools, we have assembled the publicly available ESTs for each species into a high-quality set of putative transcripts. These transcripts have been translated to produce a protein sequence resource and each is annotated with functional information derived from comparison with well-studied nematode species such as Caenorhabditis elegans and other non-nematode resources. By cross-comparing the sequences within NEMBASE4, we have also generated a protein family assignment for each translation. The data are presented in an openly accessible, interactive database. An example of the utility of NEMBASE4 is that it can examine the uniqueness of the transcriptomes of major clades of parasitic nematodes, identifying lineage-restricted genes that may underpin particular parasitic phenotypes, possible viral pathogens of nematodes, and nematode-unique protein families that may be developed as drug targets.

Proper citation: NEMBASE (RRID:SCR_006070) Copy   


http://www.ddduk.org/

The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.

Proper citation: Deciphering Developmental Disorders (RRID:SCR_006171) Copy   


http://www.port.ac.uk/research/exrc/

Supports researchers using Xenopus models. Researchers are encouraged to deposit Xenopus transgenic and mutant lines, Xenopus in situ hybridization probes, Xenopus specific antibodies and Xenopus expression clones with the Centre. EXRC staff perform quality assurance testing on these reagents and then make them available to researchers at cost. Supplies wild-type Xenopus, embryos, oocytes and Xenopus tropicalis fosmids.

Proper citation: European Xenopus Resource Center (RRID:SCR_007164) Copy   


http://www.genes2cognition.org/

A neuroscience research program that studies genes, the brain and behavior in an integrated manner, established to elucidate the molecular mechanisms of learning and memory, and shed light on the pathogenesis of disorders of cognition. Central to G2C investigations is the NMDA receptor complex (NRC/MASC), that is found at the synapses in the central nervous system which constitute the functional connections between neurons. Changes in the receptor and associated components are thought to be in a large part responsible for the phenomenon of synaptic plasticity, that may underlie learning and memory. G2C is addressing the function of synapse proteins using large scale approaches combining genomics, proteomics and genetic methods with electrophysiological and behavioral studies. This is incorporated with computational models of the organization of molecular networks at the synapse. These combined approaches provide a powerful and unique opportunity to understand the mechanisms of disease genes in behavior and brain pathology as well as provide fundamental insights into the complexity of the human brain. Additionally, Genes to Cognition makes available its biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline. The resources are freely-available to interested researchers.

Proper citation: Genes to Cognition: Neuroscience Research Programme (RRID:SCR_007121) Copy   


  • RRID:SCR_007959

    This resource has 100+ mentions.

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   


  • RRID:SCR_007891

    This resource has 1000+ mentions.

http://rfam.xfam.org/

The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome

Proper citation: Rfam (RRID:SCR_007891) Copy   


  • RRID:SCR_002105

    This resource has 10000+ mentions.

http://htslib.org/

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

Proper citation: SAMTOOLS (RRID:SCR_002105) Copy   


  • RRID:SCR_002694

    This resource has 100+ mentions.

http://www.flymine.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java API

Proper citation: FlyMine (RRID:SCR_002694) Copy   


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

Software tool to improve sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies.

Proper citation: Tract Based Spatial Statistics (RRID:SCR_024932) Copy   


  • RRID:SCR_007277

    This resource has 50+ mentions.

http://cocomac.g-node.org/main/index.php?

Online access (html or xml) to structural connectivity ("wiring") data on the Macaque brain. The database has become by far the largest of its kind, with data extracted from more than four hundred published tracing studies. The main database, contains data from tracing studies on anatomical connectivity in the macaque cerebral cortex. Also available are a variety of tools including a graphical simulation workbench, map displays and the CoCoMac-Paxinos-3D viewer. Submissions are welcome. To overcome the problem of divergent brain maps ORT (Objective Relational Transformation) was developed, an algorithmic method to convert data in a coordinate- independent way based on logical relations between areas in different brain maps. CoCoMac data is used to analyze the organization of the cerebral cortex, and to establish its structure- function relationships. This includes multi-variate statistics and computer simulation of models that take into account the real anatomy of the primate cerebral cortex. This site * Provides full, scriptable open access to the data in CoCoMac (you must adhere to the citation policy) * Powers the graphical interface to CoCoMac provided by the Scalable Brain Atlas * Sports an extensive search/browse wizard, which automatically constructs complex search queries and lets you further explore the database from the results page. * Allows you to get your hands dirty, by using the custom SQL query service. * Displays connectivity data in tabular form, through the axonal projections service. CoCoMac 2 was initiated at the Donders Institute for Brain, Cognition and Behaviour, and is currently supported by the German neuroinformatics node and the Computational and Systems Neuroscience group at the Juelich research institute.

Proper citation: CoCoMac (RRID:SCR_007277) Copy   


http://caps.ncbs.res.in/imotdb/

Comprehensive collection of spatially interacting motifs in proteins. Interacting motif database lists interacting motifs that are identified for all structural entries in PDB. Conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting common motifs shared among all superfamily members.

Proper citation: Database of Spatially Interacting Motifs in Proteins (RRID:SCR_007735) Copy   


  • RRID:SCR_010639

http://old.genedb.org/genedb/pombe/index.jsp

THIS RESOURCE IS NO LONGER IN SERVICE documented June 6, 2013 Database of all S. pombe (fission yeast) known and predicted protein coding genes, pseudogenes, transposons, tRNAs, rRNAs, snRNAs, snoRNAs and other known and predicted non-coding RNAs. Curation of new and existing literature is ongoing and changes are incorporated weekly. User feedback is welcome. The genome of fission yeast (Schizosaccharomyces pombe), which contains the smallest number of protein-coding genes yet recorded for a eukaryote: 4,824, has been sequenced and annotated. The centromeres are between 35 and 110 kilobases (kb) and contain related repeats including a highly conserved 1.8-kb element. Regions upstream of genes are longer than in budding yeast (Saccharomyces cerevisiae), possibly reflecting more-extended control regions. Some 43% of the genes contain introns, of which there are 4,730. Fifty genes have significant similarity with human disease genes; half of these are cancer related. We identify highly conserved genes important for eukaryotic cell organization including those required for the cytoskeleton, compartmentation, cell-cycle control, proteolysis, protein phosphorylation and RNA splicing. These genes may have originated with the appearance of eukaryotic life. Few similarly conserved genes that are important for multicellular organization were identified, suggesting that the transition from prokaryotes to eukaryotes required more new genes than did the transition from unicellular to multicellular organization.

Proper citation: GeneDB Spombe (RRID:SCR_010639) Copy   


http://www.cancerrxgene.org/

A genomics database project is an academic research program to identify molecular features of cancers that predict response to anti-cancer drugs.

Proper citation: Genomics of Drug Sensitivity in Cancer (RRID:SCR_011956) Copy   


  • RRID:SCR_013815

http://www.sherpa.ac.uk/romeo/index.php?la=en&fIDnum=/&mode=simple

A database which houses publisher policies regarding the self- archiving of journal articles on the web and in Open Access repositories. RoMEO contains publishers' general policies on self-archiving of journal articles and certain conference series. Each entry provides a summary of the publisher's policy, including what version of an article can be deposited, where it can be deposited, and any conditions that are attached to that deposit.

Proper citation: SHERPA RoMEO (RRID:SCR_013815) Copy   



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