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http://www.nactem.ac.uk/biolexicon/

A large-scale English terminological database that contains over 2.2.M lexical entries (3.3M semantic relations), terminological variants and rich linguistic information (subcategorization frames) which supports text mining systems. It is primarily intended to support text mining and information retrieval in the biomedical domain. The BioLexicon provides specific information to help determine the relevant facts to be extracted. BioLexicon is available in a relational database format (MySQL dump format) and it adheres to the EAGLES/ISO standards for lexical resources.

Proper citation: BioLexicon (RRID:SCR_000589) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.sharmuk.org/

A not for profit organization to accelerate research into aging by sharing resources: providing access to cost and time effective, aged murine tissue through a biorepository and database of live ageing colonies, as well as promoting the networking of researchers and dissemination of knowledge through its online collaborative environment; MiCEPACE. ShARM will provide valuable resources for the scientific community while helping to reduce the number of animals used in vital research into aging. The biobank of tissue and networking facility will enable scientists to access shared research material and data. By making use of collective resources, the number of individual animals required in research experiments can be minimized. The project also has the added value of helping to reduce the costs of research by connecting scientists, pooling resource and combining knowledge. ShARM works in partnership with MRC Harwell and the Centre for Intergrated Research into Musculoskeletal Ageing (CIMA).

Proper citation: ShARM (RRID:SCR_003120) Copy   

•   Source: SciCrunch Registry

http://caps.ncbs.res.in/3dswap/index.html

Curated knowledegbase of protein structures that are reported to be involved in 3-dimensional domain swapping. 3DSwap provides literature curated information and structure related information about 3D domain swapping in proteins. Information about swapping, hinge region, swapped region, extent of swapping, etc. are extracted from original research publications after extensive literature curation.

Proper citation: 3DSwap (RRID:SCR_004133) Copy   

•   Source: SciCrunch Registry

http://www.hgsc.bcm.tmc.edu/content/hapmap-3-and-encode-3

Draft release 3 for genome-wide SNP genotyping and targeted sequencing in DNA samples from a variety of human populations (sometimes referred to as the HapMap 3 samples). This release contains the following data: * SNP genotype data generated from 1184 samples, collected using two platforms: the Illumina Human1M (by the Wellcome Trust Sanger Institute) and the Affymetrix SNP 6.0 (by the Broad Institute). Data from the two platforms have been merged for this release. * PCR-based resequencing data (by Baylor College of Medicine Human Genome Sequencing Center) across ten 100-kb regions (collectively referred to as ENCODE 3) in 712 samples. Since this is a draft release, please check this site regularly for updates and new releases. The HapMap 3 sample collection comprises 1,301 samples (including the original 270 samples used in Phase I and II of the International HapMap Project) from 11 populations, listed below alphabetically by their 3-letter labels. Five of the ten ENCODE 3 regions overlap with the HapMap-ENCODE regions; the other five are regions selected at random from the ENCODE target regions (excluding the 10 HapMap-ENCODE regions). All ENCODE 3 regions are 100-kb in size, and are centered within each respective ENCODE region. The HapMap 3 and ENCORE 3 data are downloadable from the ftp site.

Proper citation: HapMap 3 and ENCODE 3 (RRID:SCR_004563) Copy   

•   Source: SciCrunch Registry

http://pfam.xfam.org/

A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).

Proper citation: Pfam (RRID:SCR_004726) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/gotcha/gotcha.php

GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool

Proper citation: GOtcha (RRID:SCR_005790) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/FunTree/

FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.

Proper citation: FunTree (RRID:SCR_006014) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/alien-hunter

Software for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs). The predictions (embl format) can be automatically loaded into Artemis genome viewer.

Proper citation: Alien-hunter (RRID:SCR_015967) Copy   

•   Source: SciCrunch Registry

https://www.flimfit.org/

Software package for quantitative analysis of large Fluorescence Lifetime Imaging Microscopy (FLIM) data, including global analysis. It is able to routinely analyse multi-well plate FLIM datasets on conventional PC workstations in a reasonable time., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FLIMfit (RRID:SCR_016298) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://vertebrate.genenames.org/

Software resource for vertebrate gene nomenclature. Database of gene symbols. Coordinates with vertebrate nomenclature committees, MGNC (mouse), RGNC (rat), CGNC (chicken), AGNC (Anole green lizard), XNC (Xenopus frog) and ZNC (zebrafish), to ensure genes are named in line with their human homologs.

Proper citation: VGNC (RRID:SCR_017514) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

Software command line tool for automated tractography. Standardised protocols for automated tractography in human and macaque brain.

Proper citation: XTRACT (RRID:SCR_024933) Copy   

•   Source: SciCrunch Registry

https://brainlife.io/docs/using_ezBIDS/

Web-based BIDS conversion tool to convert neuroimaging data and associated metadata to BIDS standard. Guided standardization of neuroimaging data interoperable with major data archives and platforms.

Proper citation: ezBIDS (RRID:SCR_025563) Copy   

•   Source: SciCrunch Registry

https://tristanic.github.io/isolde/

Software environment to ease task of building macromolecular models into low to medium resolution experimental maps. Physically realistic environment for model building into low-resolution electron-density maps. Can generate maps directly from crystallographic F/sigF data in MTZ format and automatically re-calculate them when model changes, and/or generate "static" maps from pre-calculated F/phi data.

Proper citation: ISOLDE (RRID:SCR_025577) Copy   

•   Source: SciCrunch Registry

https://www.ucl.ac.uk/biosciences/research/research-facilities/molecular-biology/darwin-research-facility-drf

Facility provides diverse range of equipment, expertise and training in field of biochemistry, molecular, structural and cellular biology. Facility consists of several research laboratories and support areas.

Proper citation: University College London Darwin Research Core Facility (RRID:SCR_026345) Copy   

•   Source: SciCrunch Registry

https://github.com/aametwally/Metabolic_Subphenotype_Predictor

Software repository contains code for Inference of T2D metabolic subphenotypes (MuscleIR, Beta-cell Function, Incretin Effect, Hepatic IR), Identification of dominant metabolic subphenotype, Feature extraction from glucose tiemseries, Extraction of reduced representation of glucose tiemseries,Visualization of metabolic phenotypes based on various glucose-related metrics,Concordance between CGM and Venous glucose values from at home and at clinical setting, Classification of metabolic subphenotypes.

Proper citation: Metabolic Subphenotype Predictor (RRID:SCR_027192) Copy   

•   Source: SciCrunch Registry

https://github.com/wheaton5/souporcell

Software tool to cluster cells using the genetic variants detected within the scRNAseq reads. Robust clustering of single-cell RNA-seq data by genotype without reference genotypes. Used for clustering scRNAseq by genotypes.

Proper citation: Souporcell (RRID:SCR_027462) Copy   

•   Source: SciCrunch Registry