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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.
A versatile web-server application for the analysis and visualization of array-CGH data.
Proper citation: waviCGH (RRID:SCR_006662) Copy
http://www.imgt.org/IMGTindex/LIGM.html
IMGT/LIGM-DB is a comprehensive database of immunoglobulin (IG) and T cell receptor (TR) nucleotide sequences from human and other vertebrate species (270). IMGT/LIGM-DB includes all germline (non-rearranged) and rearranged IG and TR genomic DNA (gDNA) and complementary DNA (cDNA) sequences published in generalist databases. IMGT/LIGM-DB allows searches from the Web interface according to biological and immunogenetic criteria through five distinct modules depending on the user interest. Users can search the catalogue by accession number, mnemonic, definition, creation date, length, or annotation level. They also have the option to search through taxonomic classification, keywords, and annotated labels. For a given entry, nine types of display are available including the IMGT flat file, the translation of the coding regions and the analysis by the IMGT/V-QUEST tool (see parent org. below). IMGT/LIGM-DB distributes expertly annotated sequences. The annotations hugely enhance the quality and the accuracy of the distributed detailed information. They include the sequence identification, the gene and allele classification, the constitutive and specific motif description, the codon and amino acid numbering, and the sequence obtaining information, according to the main concepts of IMGT-ONTOLOGY. They represent the main source of IG and TR gene and allele knowledge stored in IMGT/GENE-DB and in the IMGT reference directory., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: IMGT/LIGM-DB (RRID:SCR_006931) Copy
Database that collects all arabidopsis transcription factors (totally 1922 Loci; 2290 Gene Models) and classifies them into 64 families. It uses not only locus (gene), but also gene model (transcript, protein) and the detail information is for each gene model not for locus. It adds multiple alignment of the DNA-binding domain of each family, Neighbor-Joining phylogenetic tree of each family, the GO annotation, homolog with the Database of Rice Transcription Factors (DRTF). It also keeps old information items such as the unique cloned and sequenced information of about 1200 transcription factors, protein domains, 3D structure information with BLAST hits against PDB, predicted Nuclear Location Signals, UniGene information, as well as links to literature reference.
Proper citation: Database of Arabidopsis Transcription Factors (RRID:SCR_007101) Copy
http://www.polygenicpathways.co.uk
Database of disease genes and risk factors and of host pathogen/interactomes. Lists genes, pathways and environmental risk factors positively associated with diseases and conditions such as Alzheimer's disease, schizophrenia, multiple sclerosis, childhood obesity, anorexia nervosa, HIV-1/AIDS, and helicobacter pylori. Details of polymorphisms as well as negative/positive association data can be found via Useful links. Throughout the site are links to Entrez Gene and Pubmed.
Proper citation: Polygenic Pathways (RRID:SCR_006962) Copy
Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.
Proper citation: CRCView (RRID:SCR_007092) Copy
http://www.broadinstitute.org/mammals/haploreg/haploreg.php
HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.
Proper citation: HaploReg (RRID:SCR_006796) Copy
http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home
A web-based resource that facilitates rapid analysis of exon sequences to identify putative exonic splicing enhancers (ESEs) responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.
Proper citation: ESEfinder 3.0 (RRID:SCR_007088) Copy
http://urgv.evry.inra.fr/CATdb
CATdb collects together all the information on transcriptome experiments done at URGV with CATMA micro arrays. All data in CATdb come from the URGV micro array platforms. Common procedures are used including any steps from the experiment design to the statistical analyses. Directed through a WEB interface, biologists enter the standard description of each experimental step (extraction, labelling, hybridization and scanning). Then, normalization and statistical analyses are done following a set of selected methods depending on the experimental design and array types.
Proper citation: CATdb: a Complete Arabidopsis Transcriptome database (RRID:SCR_007582) Copy
http://www.allelefrequencies.net
The main purpose of the allelefrequencies.net website is to provide one central source, freely available to all. For the storage of allele frequencies from different polymorphic areas in the HUMAN genome. Users can contribute the results of their work into one common database, and can perform database searches on information already available. They have currently collected data in allele, haplotype and genotype format. The success of this website will depend on you to contribute your data. Sponsors: This resource is supported Royal Liverpool University. Keywords: Allele, Polymorphic, Genome, Database, Data, Haplotype, Genotype,
Proper citation: Allele Frequencies in Worldwide Populations (RRID:SCR_007259) Copy
https://gitlab.com/kyrgyzov/lsa_slurm
Software tool to implement pre-assembly binning scheme leveraging sparse dictionary learning and matrix factorization to solve sparse decomposition problems arising in field of metagenomics.
Proper citation: lsa_slurm (RRID:SCR_018134) Copy
Ratings or validation data are available for this resource
http://broadinstitute.github.io/picard/
Java toolset for working with next generation sequencing data in the BAM format.
Proper citation: Picard (RRID:SCR_006525) Copy
A collection of bioinformatics tools that can be pieced together in a very easy and flexible manner to perform both simple and complex tasks. The Biopieces work on a data stream in such a way that the data stream can be passed through several different Biopieces, each performing one specific task: modifying or adding records to the data stream, creating plots, or uploading data to databases and web services. The Biopieces are executed in a command line environment where the data stream is initialized by specific Biopieces which read data from files, databases, or web services, and output records to the data stream that is passed to downstream Biopieces until the data stream is terminated at the end of the analysis. The advantage of the Biopieces is that a user can easily solve simple and complex tasks without having any programming experience. Moreover, since the data format used to pass data between Biopieces is text based, different developers can quickly create new Biopieces in their favorite programming language - and all the Biopieces will maintain compatibility. Finally, templates exist for creating new Biopieces in Perl and Ruby. There are currently ~190 Biopieces (March 2014).
Proper citation: Biopieces (RRID:SCR_005783) Copy
http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html
VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: VIDA (RRID:SCR_007111) Copy
http://cudasw.sourceforge.net/
CUDASW++ is a bioinformatics software for Smith-Waterman protein database searches that takes advantage of the massively parallel CUDA architecture of NVIDIA Tesla GPUs to perform sequence searches 10x-50x faster than NCBI BLAST. In this algorithm, we deeply explore the SIMT (Single Instruction, Multiple Thread) and virtualized SIMD (Single Instruction, Multiple Data) abstractions to achieve fast speed. This algorithm has been fully tested on Tesla C1060, Tesla C2050, GeForce GTX 280 and GTX 295 graphics cards, and has been incorporated to NVIDIA Tesla Bio Workbench. * Operating System: Linux * Programming language: CUDA and C * Other requirements: CUDA SDK and Toolkits 2.0 or higher
Proper citation: CUDASW++ (RRID:SCR_008862) Copy
http://www-stat.stanford.edu/~tibs/SAM/
Software for genomic expression data mining using a statistical technique for finding significant genes in a set of microarray experiments.
Proper citation: SAM (RRID:SCR_010951) Copy
http://bioen-compbio.bioen.illinois.edu/FusionHunter/
Software for identifying fusion transcripts using paired-end RNA-seq.
Proper citation: FusionHunter (RRID:SCR_011895) Copy
http://bioinformatics.org/biococoa/
Open source framework for bioinformatics written in Objective-C. Provides Cocoa and GNUstep programmers with full suite of APIs for handling and manipulating biological sequences.
Proper citation: BioCocoa (RRID:SCR_023977) Copy
http://biblatex-biber.sourceforge.net/
Software bibliography processing backend for LaTeX biblatex package. Supports unsurpassed feature set for automated conformance to complex bibliography style requirements such as labelling, sorting and name handling. BibTeX replacement for users of BibLaTeX.
Proper citation: Biber (RRID:SCR_023973) Copy
http://johnhommer.com/academic/code/aghermann
Sotware tool designed to run Process S simulations on Slow Wave Activity profiles from human EEG recordings.Produces set of sleep homeostat parameters which can be used to describe and differentiate individual sleepers, such as short vs long sleepers, early vs late, etc.Sleep research experiment manager, with facility for reading, displaying, and manual and semi-automatic scoring EEG recordings in edf format; conventional PSD and EEG Microcontinuity profiles; artifact detection; Independent Component Analysis; basic sleep analysis NREM-REM cycle detection.
Proper citation: Aghermann (RRID:SCR_023965) Copy
https://metacpan.org/dist/Bio-ASN1-EntrezGene
Software regular expression based Perl Parser for NCBI Entrez Gene genome databases. Parses ASN.1-formatted Entrez Gene record and returns data structure that contains all data items from gene record.
Proper citation: Bio-ASN1-EntrezGene (RRID:SCR_024056) Copy
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