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http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

•   Source: SciCrunch Registry

http://www.imgt.org/IMGTindex/IMGTgene-db.html

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IMGT/GENE-DB (RRID:SCR_006964) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/edmr/

Comprehensive differentially methylated regions (DMR) analysis based on bimodal normal distribution model and weighted cost function for regional methylation analysis optimization.

Proper citation: eDMR (RRID:SCR_006960) Copy   

•   Source: SciCrunch Registry

http://www.vbase2.org/

Integrative database of germ-line V genes from the immunoglobulin loci of human and mouse. It presents V gene sequences extracted from the EMBL nucleotide sequence database and Ensembl together with links to the respective source sequences. Based on the properties of the source sequences, V genes are classified into 3 different classes: * Class 1: genomic and rearranged evidence * Class 2: genomic evidence only * Class 3: rearranged evidence only This allows careful sequence quality validation by the user. References to other immunological databases ( KABAT, IMGT/LIGM and VBASE ) are given to provide all public annotation data for each V gene. The VBASE2 database can be accessed either by the Direct Query interface or by the DNAPLOT Query interface. The Sequences given by the user are aligned with DNAPLOT against the VBASE2 database. Direct Query allows to enter sequence IDs and names (Field 1), choose species, locus, V gene family and class (Field 2) or search for 100% sequences (Field 3). At the DNAPLOT Query, the sequences given by the user are aligned with DNAPLOT against the VBASE2 database. The DNAPLOT program offers V gene nucleotide sequence alignment referring to the IMGT V gene unique numbering. The Quick Search can be used either for Direct Query to search for sequence IDs and V gene names or for DNAPLOT Query for up to 5 sequences. The new Fab Analysis allows you to align Fab, scFab, scAb or scFv sequences with DNAPLOT against the VBASE2 database, where both heavy and light chain are analyzed.

Proper citation: VBASE2 (RRID:SCR_007082) Copy   

•   Source: SciCrunch Registry

https://github.com/steinmann/peakzilla

An algorithm to identify transcription factor binding sites from ChIP-seq data.

Proper citation: Peakzilla (RRID:SCR_007471) Copy   

•   Source: SciCrunch Registry

http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/ampliconnoise/

A collection of programs for the removal of noise from 454 sequenced PCR amplicons. This project also includes the Perseus algorithm for chimera removal.

Proper citation: AmpliconNoise (RRID:SCR_007814) Copy   

•   Source: SciCrunch Registry

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

Gene Expression Atlas is a semantically enriched database of meta-analysis based summary statistics over a curated subset of ArrayExpress Archive, servicing queries for condition-specific gene expression patterns as well as broader exploratory searches for biologically interesting genes/samples. The EBI Gene Expression Atlas Blog discusses ideas, features and problems of creating a large scale meta-analytical atlas of gene expression from publicly available microarray data. Atlas REST API provides all the results available in the main web application in a pragmatic, easy to use form - simple HTTP GET queries as input and either JSON or XML formats as output. Gene Expression Atlas goals: 1. Provision of a statistically robust framework for integration of gene expression experiment results across different platforms at a meta-analytical level 2. A simple interface for identifying strong differential expression candidate genes in conditions of interest 3. Integration of ontologies for high quality annotation of gene and sample attributes 4. Construction of new gene expression summarized views, with a view to analysis of putative signaling pathway targets, discovery of correlated gene expression patterns and the identification of condition/tissue-specific patterns of gene expression.

Proper citation: Gene Expression Atlas (RRID:SCR_007989) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/info/docs/tools/vep/index.html

Data analysis service to predict the functional consequences of known and unknown variants.

Proper citation: Variant Effect Predictor (RRID:SCR_007931) Copy   

•   Source: SciCrunch Registry

http://cbil.upenn.edu/RUM/

An alignment, junction calling, and feature quantification pipeline specifically designed for Illumina RNA-Seq data.

Proper citation: RUM (RRID:SCR_008818) Copy   

•   Source: SciCrunch Registry

https://github.com/armintoepfer/QuasiRecomb/releases

A jumping hidden Markov model that describes the generation of the viral quasispecies and a method to infer its parameters by analysing next generation sequencing data.

Proper citation: QuasiRecomb (RRID:SCR_008812) Copy   

•   Source: SciCrunch Registry

https://genome.unc.edu/xpn/

Merging Two Gene Expression Studies via Cross Platform Normalization.

Proper citation: XPN (RRID:SCR_008845) Copy   

•   Source: SciCrunch Registry

http://tvap.genome.wustl.edu/tools/music/

A set of tools aimed at determining the significance of somatic mutations discovered within a given cohort of cancer samples, incorporating the cohort''s alignment data, variant lists and any relevant clinical data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MuSiC (RRID:SCR_008792) Copy   

•   Source: SciCrunch Registry

http://research-pub.gene.com/gmap/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A software program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

Proper citation: GMAP (RRID:SCR_008992) Copy   

•   Source: SciCrunch Registry

http://bioinfo.au.tsinghua.edu.cn/software/seqsaw/

A package for mapping of spliced reads and unbiased detection of novel splice junctions from RNA-seq data.

Proper citation: SeqSaw (RRID:SCR_009185) Copy   

•   Source: SciCrunch Registry

http://wpicr.wpic.pitt.edu/WPICCompGen/bars.htm

Software application that is a statistical method that bridges the gap between single-locus and haplotype-based tests of association. It is based on the non-parametric regression techniques embodied by Bayesian Adaptive Regression Splines. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARS (RRID:SCR_009123) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/services/NetOGlyc/

Server that produces predictions of mucin-type GalNAc O-glycosylation sites in mammalian proteins.

Proper citation: NetOGlyc (RRID:SCR_009026) Copy   

•   Source: SciCrunch Registry

http://elastix.isi.uu.nl/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023. Software toolbox for rigid and nonrigid registration of images. elastix is open source software, based on the well-known Insight Segmentation and Registration Toolkit (ITK). The software consists of a collection of algorithms that are commonly used to solve (medical) image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. A command-line interface enables automated processing of large numbers of data sets, by means of scripting. A paper describing elastix contains more details: S. Klein, M. Staring, K. Murphy, M.A. Viergever, J.P.W. Pluim, elastix: a toolbox for intensity based medical image registration,; IEEE Transactions on Medical Imaging, vol. 29, no. 1, pp. 196 - 205, January 2010., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: elastix (RRID:SCR_009619) Copy   

•   Source: SciCrunch Registry

http://mocklerlab.org/tools/1

An application for discovering potential splice junctions in high throughput sequencing (HTS) data.

Proper citation: Supersplat (RRID:SCR_009826) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IMGT-ONTOLOGY

Ontology for immunogenetics and immunoinformatics. Provides semantic specification of terms to be used in immunogenetics and immunoinformatics and manages related knowledge, thus allowing standardization for immunogenetics data from genome, proteome, genetics, two-dimensional (2D) and three-dimensional (3D) structures. Manages the knowledge through diverse facets relying on seven axioms, IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, LOCALIZATION, ORIENTATION and OBTENTION. These axioms postulate that any object, any process and any relation can be identified, classified, described, numbered, localized and orientated, and the way it is obtained can be characterized. The axioms constitute the Formal IMGT-ONTOLOGY, also designated as IMGT-Kaleidoscope. As the same axioms can be used to generate concepts for multi-scale level approaches, the Formal IMGT-ONTOLOGY represents a paradigm for system biology ontologies, which need to identify, to classify, to describe, to number, to localize and to orientate objects, processes and relations at the molecule, cell, tissue, organ, organism or population levels. IMGT, the international ImMunoGeneTics information system, has been built on IMGT-ONTOLOGY. The version 1.0.2 of IMGT-ONTOLOGY includes the concepts of IDENTIFICATION and the concepts of CLASSIFICATION.

Proper citation: IMGT-ONTOLOGY (RRID:SCR_010342) Copy   

•   Source: SciCrunch Registry