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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.
https://www.sanger.ac.uk/science/tools/caf
Software tools for manipulating Common Assembly Format files text format for describing sequence assemblies,that can be downloaded from the Sanger ftp site.
Proper citation: caftools (RRID:SCR_023982) Copy
http://ingenium.home.xs4all.nl/dicom.html
Software for DICOM training and testing,Demonstration and research image archives,Image format conversion from scanner with DICOM network access,DICOM image viewing and slide making, DICOM image selection, (limited) editing, and splitting and merging of series, Advanced scriptable image modification, filtering, forwarding and conversion, DICOM caching and archive merging, DICOM web access for viewing and data management (scriptable),Connection to Lua IDE for all sorts of DICOM manipulation.
Proper citation: Conquest DICOM (RRID:SCR_023993) Copy
https://github.com/pennsignals/chime
Software designed to assist hospitals and public health officials with understanding hospital capacity needs as they relate to the COVID pandemic. CHIME enables capacity planning by providing estimates of total daily and running totals of inpatient hospitalizations, ICU admissions, and patients requiring ventilation.
Proper citation: CHIME (RRID:SCR_023987) Copy
https://genome.sph.umich.edu/wiki/EMMAX
Software statistical test for large scale human or model organism association mapping accounting for the sample structure. In addition to the computational efficiency obtained by EMMA algorithm, EMMAX takes advantage of the fact that each loci explains only a small fraction of complex traits, which allows us to avoid repetitive variance component estimation procedure, resulting in a significant amount of increase in computational time of association mapping using mixed model.
Proper citation: EMMAX (RRID:SCR_024012) Copy
Software extensible open source radiation therapy research platform based on the DICOM standard. It also functions as a cross-platform DICOM RT viewer.
Proper citation: dicompyler (RRID:SCR_024006) Copy
https://cran.r-project.org/web/packages/foreign/index.html
Software tool for reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
Proper citation: foreign (RRID:SCR_024025) Copy
https://github.com/rrwick/Deepbinner
Software tool for demultiplexing barcoded Oxford Nanopore sequencing reads.Signal level demultiplexer for Oxford Nanopore reads.
Proper citation: Deepbinner (RRID:SCR_024001) Copy
http://img.jgi.doe.gov/cgi-bin/m/main.cgi
Resource for analysis and annotation of genome and metagenome datasets in comprehensive comparative context. IMG provides users with tools for analyzing publicly available genome datasets and metagenome datasets.
Proper citation: IMG System (RRID:SCR_002965) Copy
http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/
A system of databases which stores information on the influence of mutations in regulatory gene regions . This tool helps recognize protein binding sites that are being altered by mutation. It has four cross-linked sub databases that focus on specific aspects including: (1) the effect of single nucleotide mutations in regulatory gene regions and their interaction with nuclear proteins; (2) references to original publications on the subject; (3) the experimental details of these publications; and (4) the protocols of these experiments. This resource is aimed at providing information to further research on the influence of specific sequence alterations on disease susceptibility, drug resistance and healthcare.
Proper citation: rSNP Guide (RRID:SCR_000087) Copy
Manually curated, comprehensive repository of experimentally characterized bacterial glycoproteins and archaeal glycoproteins, generated from an exhaustive literature search. This is the focused effort to provide concise relevant information derived from rapidly expanding literature on prokaryotic glycoproteins, their glycosylating enzyme(s), glycosylation linked genes, and genomic context thereof, in a cross-referenced manner. The database is arranged into two sections namely, ProCGP and ProUGP. ProCGP is the main section containing characterized prokaryotic glycoproteins, defined as entries with at least one experimentally known glycosylated residue (glycosite). Whereas, ProUGP is the supplementary section, presenting uncharacterized prokaryotic glycoproteins, defined as entries with experimentally identified glycosylation but unidentified glycosites. The ProGlycProt has been developed with to aid and advance the emerging scientific interests in understanding the mechanisms, implications, and novelties of protein glycosylation in prokaryotes that include many pathogenic as well as economically important bacterial species. The website supports a dedicated structure gallery of homology models and crystal structures of characterized glycoproteins in addition to two new tools developed in view of emerging information about prokaryotic sequons (conserved sequences of amino acids around glycosites) that are never or rarely seen in eukaryotic glycoproteins. ProGlycProt provides an extensive compilation of experimentally identified glycosites (334) and glycoproteins (340) of prokaryotes that could serve as an information resource for research and technology applications in glycobiology. A general data update policy is once in three months. Existing entries are updated in real-time.
Proper citation: ProGlycProt (RRID:SCR_000622) Copy
http://www.ncbi.nlm.nih.gov/dbSTS/
THIS RESOURCE IS NO LONGER IN SERVICE, as of October 1, 2013; however, the site is still accessible. NCBI resource that contains sequence and mapping data on short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. The dbSTS database offers a route for submission of STS sequences to GenBank. It is designed especially for the submission of large batches of STS sequences.
Proper citation: dbSTS (RRID:SCR_000400) Copy
http://interolog.gersteinlab.org/
Interolog/Regulog quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins.
Proper citation: Interolog/Regulog Database (RRID:SCR_000755) Copy
http://www.bioguo.org/AnimalTFDB/
A comprehensive transcription factor (TF) database in which they identified and classified all the genome-wide TFs in 50 sequenced animal genomes (Ensembl release version 60). In addition to TFs, it also collects transcription co-factors and chromatin remodeling factors of those genomes, which play regulatory roles in transcription. Here they defined the TFs as proteins containing a sequence-specific DNA-binding domain (DBD) and regulating target gene expression. Currently, the AnimalTFDB classifies all the animal TFs into 72 families according to their conserved DBDs. Gene lists of transcription factors, transcription co-factors and chromatin remodeling factors of each species are available for downloading., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: AnimalTFDB (RRID:SCR_001624) Copy
https://www.hgmd.cf.ac.uk/ac/introduction.php?lang=english
Curated database of known (published) gene lesions responsible for human inherited disease.
Proper citation: Human Gene Mutation Database (RRID:SCR_001621) Copy
http://pallab.serc.iisc.ernet.in/gester/
Database of intrinsic terminators of transcription that is comprized of >2,200,000 bacterial terminators identified from a total of 2036 chromosomes and 1508 plasmids. Information about structural parameters of individual terminators such as sequence, length of stem and loop, mismatches and gaps, U-trail, genomic coordinates and gene name and accession number is available in both tabular form and as a composite figure. Summary statistics for terminator profiles of whole genome can be also obtained. Raw data files for individual genomes can be downloaded (.zip files) for detailed investigations. Data is organized into different tiers such that users can fine-tune their search by entering name of the species, or taxon ID or genomes with a certain number of terminators. To visualize the occurrence of the terminators, an interactive map, with the resolution to single gene level, has been developed.
Proper citation: WebGeSTer DB (RRID:SCR_002165) Copy
It helps users retrieve information on genes and proteins. The underlying structure of PubGene can be viewed as a gene-centric database. Gene and protein names are cross-referenced to each other and to terms that are relevant to understanding their biological function, importance in disease and relationship to chemical substances. The result is a literature network organizing information in a form that is easy to navigate.
Proper citation: PubGene (RRID:SCR_002119) Copy
http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/
Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.
Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy
A database that curates new experimental and bioinformatic information about the genes and gene products of the model bacterium Escherichia coli K-12 strain MG1655. It has been created to integrate information from post-genomic experiments into a single resource with the aim of providing functional predictions for the 1500 or so gene products for which we have no knowledge of their physiological function. While EchoBASE provides a basic annotation of the genome, taken from other databases, its novelty is in the curation of post-genomic experiments and their linkage to genes of unknown function. Experiments published on E. coli are curated to one of two levels. Papers dealing with the determination of function of a single gene are briefly described, while larger dataset are actually included in the database and can be searched and manipulated. This includes data for proteomics studies, protein-protein interaction studies, microarray data, functional genomic approaches (looking at multiple deletion strains for novel phenotypes) and a wide range of predictions that come out of in silico bioinformatic approaches. The aim of the database is to provide hypothesis for the functions of uncharacterized gene products that may be used by the E. coli research community to further our knowledge of this model bacterium.
Proper citation: EchoBASE (RRID:SCR_002430) Copy
http://www.tanpaku.org/autophagy/
Database that provides basic, up-to-date information on relevant literature, and a list of autophagy-related proteins and their homologs in eukaryotes.
Proper citation: Autophagy Database (RRID:SCR_002671) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. Database of known and predicted protein domain (domain-domain) interactions containing interactions inferred from PDB entries, and those that are predicted by 8 different computational approaches using Pfam domain definitions. DOMINE contains a total of 26,219 domain-domain interactions (among 5,410 domains) out of which 6,634 are inferred from PDB entries, and 21,620 are predicted by at least one computational approach. Of the 21,620 computational predictions, 2,989 interactions are high-confidence predictions (HCPs), 2,537 interactions are medium-confidence predictions (MCPs), and the remaining 16,094 are low-confidence predictions (LCPs). (May 2014)
Proper citation: DOMINE: Database of Protein Interactions (RRID:SCR_002399) Copy
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