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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://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi

This server provides programs, web services, and databases, related to our work on RNA secondary structures. For general information and other offerings from our group see the main TBI web server. With the 1st of May 2009 we updated our servers to the Vienna RNA package version 1.8.2! The Vienna RNA Servers: * RNAfold server predicts minimum free energy structures and base pair probabilities from single RNA or DNA sequences. * RNAalifold server predicts consensus secondary structures from an alignment of several related RNA or DNA sequences. You need to upload an alignment. * RNAinverse server allows you to design RNA sequences for any desired target secondary structure. * RNAcofold server allows you to predict the secondary structure of a dimer. * RNAup server allows you to predict the accessibility of a target region. * LocARNA server generates structural alignments from a set of sequences. In collaboration with the Bioinformatics Group Freiburg. * barriers server allows you to get insights into RNA folding kinetics. * RNAz server will assist you in detecting thermodynamically stable and evolutionarily conserved RNA secondary structures in multiple sequence alignments. * Structure conservation analysis server will assist you in detecting evolutionarily conserved RNA secondary structures in multiple sequence alignments. * RNAstrand server allows you to predict the reading direction of evolutionarily conserved RNA secondary structures. * RNAxs server assists you in siRNA design. * Bcheck predicts rnpB genes Downloads Get the Source code for: * the Vienna RNA Package, our basic RNA secondary structure analysis software. * The ALIDOT package for finding conserved structure motifs (add-on) * The barriers program for analysis of RNA folding landscapes. Databases * Atlas of conserved Viral RNA Structures found by ALIDOT

Proper citation: Vienna RNA (RRID:SCR_008550) Copy   

•   Source: SciCrunch Registry

http://lowelab.ucsc.edu/tRNAscan-SE

Web server to search for tRNA genes in genomic sequence. If you would like to run tRNAscan-SE locally, you can get the UNIX source code (gzip''d tar file).

Proper citation: tRNAscan-SE (RRID:SCR_008637) Copy   

•   Source: SciCrunch Registry

http://steps.sourceforge.net/STEPS/default.php

STEPS is a package for exact stochastic simulation of reaction-diffusion systems in realistic, complex 3D geometries. Our core simulation algorithm is an efficient implementation of a variation on Gillespie''s SSA, extended to deal with diffusion of molecules over the elements of a 3D tetrahedral mesh. While it was mainly developed for simulating detailed models of neuronal signaling pathways in dendrites and around synapses, it is a general tool and can be used for studying any biochemical pathway in which spatial gradients and morphology are thought to play a role. We have implemented STEPS as a set of Python modules, which means STEPS users can use Python scripts to control all aspects of setting up the model, generating a mesh, controlling the simulation and generating and analyzing output. The core computational routines are still implemented as C/C++ extension modules for maximal speed of execution.

Proper citation: STEPS (RRID:SCR_008742) Copy   

•   Source: SciCrunch Registry

http://iubio.bio.indiana.edu:8089/

Provides summary of gene and genomic information from eukaryotic organism databases. This includes gene symbol and full name, chromosome, genetic and molecular map information, Gene Ontology (Function/Location/Process) and gene homology, product information, links to extended gene information.

Proper citation: Eukaryote Genes (RRID:SCR_008617) 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://woldlab.caltech.edu/rnaseq

Software for Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq. Its functions are to (i) assign reads that map uniquely in the genome to their site of origin and, for reads that match equally well to several sites (''multireads''), assign them to their most likely site(s) of origin; (ii) detect splice-crossing reads and assign them to their gene of origin; (iii) organize reads that cluster together, but do not map to an already known exon, into candidate exons or parts of exons; and (iv) calculate the prevalence of transcripts from each known or newly proposed RNA, based on normalized counts of unique reads, spliced reads and multireads. The new candidate RNA regions produced can be thought of as ESTs, and, like ESTs, some are provisionally appended to existing gene models if they meet several additional criteria. Remaining unassigned candidate transcribed regions (labeled RNAFAR features) can then be used in conjunction with other confirming data to develop new or revised gene models.

Proper citation: ERANGE (RRID:SCR_005240) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/rna-seqc

Java software which computes a series of quality control metrics for RNA-seq data and can compare sequencing quality across different samples or experiments to evaluate different experimental parameters. The input can be one or more BAM files, and the output consists of HTML reports and tab delimited files of metrics data.

Proper citation: RNA-SeQC (RRID:SCR_005120) Copy   

•   Source: SciCrunch Registry

http://cbrc.kaust.edu.sa/readscan/

A highly scalable parallel software program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets.

Proper citation: READSCAN (RRID:SCR_005204) Copy   

•   Source: SciCrunch Registry