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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage

Database of genomes at various stages of completion, from early access to partial genomes with automatic annotation through to complete genomes with extensive manual curation. Its primary goals are: 1) to provide reliable access to the latest sequence data and annotation/curation for the whole range of organisms sequenced by the Pathogen group, and 2) to develop the website and other tools to aid the community in accessing and obtaining the maximum value from these data.

Proper citation: GeneDB (RRID:SCR_002774) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/c-zhou/yahs

Software command line tool for construction of chromosome scale scaffolds from Hi-C data. Scaffolding tool using Hi-C or Omni-C data. Used to scaffold contig level assemblies into chromosome scale scaffolded assemblies.

Proper citation: YaHS (RRID:SCR_022965) Copy   

•   Source: SciCrunch Registry

http://tiger.bsc.es

Resource enables integrative exploration of genetic and epigenetic basis of development of Type 2 Diabetes, together with other associated functional, molecular and clinical data, centered in biology and role of pancreatic beta cells.The gene expression regulatory variation landscape of human pancreatic islets.

Proper citation: TIGER Data Portal (RRID:SCR_023626) Copy   

•   Source: SciCrunch Registry

https://github.com/mskcc/lohhla

Software tool to evaluate HLA loss using next-generation sequencing data. Computational tool to determine HLA allele-specific copy number from sequencing data.

Proper citation: LOHHLA (RRID:SCR_023690) Copy   

•   Source: SciCrunch Registry

http://shiny.chemgrid.org/boxplotr/

Web tool written in R for generation of box plots with R packages shiny, beanplot4, vioplot, beeswarm and RColorBrewer, and hosted on shiny server to allow for interactive data analysis. Data are held temporarily and discarded as soon as session terminates.Represents both summary statistics and distribution of primary data. Enables visualization of minimum, lower quartile, median, upper quartile and maximum of any data set.Data matrix can be uploaded as file or pasted into application. May be downloaded to run locally or as virtual machine for VMware and VirtualBox.

Proper citation: BoxPlotR (RRID:SCR_015629) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SpydrPick

Software command line tool for performing direct coupling analysis of aligned categorical datasets. Used for analysis at scale of pan genomes of many bacteria. Incorporates correction for population structure, which adjusts for phylogenetic signal in data without requiring explicit phylogenetic tree.

Proper citation: SpydrPick (RRID:SCR_018176) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SuperDCA

Software tool for global direct coupling analysis of input genome alignments. Implements variant of pseudolikelihood maximization direct coupling analysis, with emphasis on optimizations that enable its use on genome scale. May be used to discover co evolving pairs of loci.Used for genome wide epistasis analysis.

Proper citation: SuperDCA (RRID:SCR_018175) Copy   

•   Source: SciCrunch Registry

http://enterobase.warwick.ac.uk/

Integrated software environment that supports identification of global population structures within several bacterial genera that include pathogens. Web service for analyzing and visualizing genomic variation within bacteria. Genome database to enable to identify, analyse, quantify and visualise genomic variation within bacterial genera including Salmonella, Escherichia/Shigella, Clostridioides,Vibrio,Yersinia,Helicobacter,Moraxella.

Proper citation: EnteroBase (RRID:SCR_019019) Copy   

•   Source: SciCrunch Registry

http://crosslinkviewer.org/

Open source web based visualization tool for exploring crosslinking mass spectrometry results. Displays residue resolution positional information including linkage sites and linked peptides, all types of crosslinking reaction product, ambiguous results and additional sequence information such as domains.

Proper citation: xiNET (RRID:SCR_021010) Copy   

•   Source: SciCrunch Registry

https://github.com/sanger-pathogens/Bio-Tradis

Analysis software for the output from TraDIS (Transposon Directed Insertion Sequencing) analyses of dense transposon mutant libraries. The Bio-Tradis analysis pipeline is implemented as an extensible Perl library which can either be used as is, or as a basis for the development of more advanced analysis tools.

Proper citation: Bio-tradis (RRID:SCR_015993) Copy   

•   Source: SciCrunch Registry

http://bids.neuroimaging.io

Standard specification for organizing and describing outputs of neuroimaging experiments. Used to organize and describe neuroimaging and behavioral data by neuroscientific community as standard to organize and share data. BIDS prescribes file naming conventions and folder structure to store data in set of already existing file formats. Provides standardized templates to store associated metadata in form of Javascript Object Notation (JSON) and tab-separated value (TSV) files. Facilitates data sharing, metadata querying, and enables automatic data analysis pipelines. System to curate, aggregate, and annotate neuroimaging databases. Intended for magnetic resonance imaging data, magnetoencephalography data, electroencephalography data, and intracranial encephalography data.

Proper citation: Brain Imaging Data Structure (BIDs) (RRID:SCR_016124) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/SC3.html

Software tool for the unsupervised clustering of cells from single cell RNA-Seq experiments. SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.

Proper citation: SC3 (RRID:SCR_015953) Copy   

•   Source: SciCrunch Registry