Tools   Select Another Resource Report Type

https://medschool.ucsd.edu/Pages/default.aspx

Graduate medical school of University of California, San Diego. It was the third medical school in the University of California system, after those established at UCSF and UCLA, and is the only medical school in the San Diego metropolitan area.

Proper citation: University of California San Diego School of Medicine; California; USA (RRID:SCR_010634) Copy   

•   Source: SciCrunch Registry

http://www.abbvie.com/

A research-based biopharmaceutical company that develops advanced therapies to address global health problems.

Proper citation: AbbVie (RRID:SCR_010484) Copy   

•   Source: SciCrunch Registry

http://www.cbrc.kaust.edu.sa/hmcan/

A Hidden Markov Model based software tool that is developed to detect histone modification in cancer ChIP-seq data.

Proper citation: HMCan (RRID:SCR_010858) Copy   

•   Source: SciCrunch Registry

http://bcb.cs.tufts.edu/dflat/

We are an interdisciplinary team dedicated to annotating gene function related to human fetal development. We are contributing new functional annotation to the Gene Ontology, curating and mining gene sets suitable for the interpretation of developmental genomic data, and creating the computational tools needed to apply genomics for better understanding the molecular mechanisms of human development. Our GO annotation is in the process of being incorporated into the GOA public release. The GONE (Gene Ontology Non-Eligible) database is where we store annotations relevant to our research but that don''t quite meet GOA''s standards. Usually an annotation falls into this category because either the gene/protein described is a family of genes/proteins rather than a specific one, there is no UniProt ID to identify the gene/protein in the system, a GO term does not yet exist to describe the particular function, process, or location of the gene/protein, the species is not clearly identifiable in the paper, or the evidence is not as reliable (GO evidence codes TAS and NAS). As individual annotations these are more suspect than current GO annotation. However, for functional analysis of expression data, these gene sets can be valuable even with a certain amount of noise. We also include here a link to the supplementary data from our forthcoming PSB 2011 paper on gene set mining.

Proper citation: DFLAT (RRID:SCR_010738) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/cgi-bin/tess/tess

TESS is a web tool for predicting transcription factor binding sites in DNA sequences. It can identify binding sites using site or consensus strings and positional weight matrices from the TRANSFAC, JASPAR, IMD, and our CBIL-GibbsMat database. You can use TESS to search a few of your own sequences or for user-defined CRMs genome-wide near genes throughout genomes of interest. Search for CRMs Genome-wide: TESS now has the ability to search whole genomes for user defined CRMs. Try a search in the AnGEL CRM Searches section of the navigation bar.. You can search for combinations of consensus site sequences and/or PWMs from TRANSFAC or JASPAR. Search DNA for Binding Sites: TESS also lets you search through your own sequence for TFBS. You can include your own site or consensus strings and/or weight matrices in the search. Use the Combined Search under ''Site Searches'' in the menu or use the box for a quick search. TESS assigns a TESS job number to all sequence search jobs. The job results are stored on our server for a period of time specified in the search submit form. During this time you may recall the search results using the form on this page. TESS can also email results to you as a tab-delimited file suitable for loading into a spreadsheet program. Query for Transcription Factor Info: TESS also has data browsing and querying capabilities to help you learn about the factors that were predicted to bind to your sequence. Use the Query TRANSFAC or Query Matrices links above or use the search interface provided from the home page.

Proper citation: TESS: Transcription Element Search System (RRID:SCR_010739) Copy   

•   Source: SciCrunch Registry

http://mirtar.mbc.nctu.edu.tw/human/

An integrated web server for identifying miRNA-target interactions in human. The tool enables biologists easily to identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. It also provides perspective of information on the miRNA targets on alternatively spliced transcripts.

Proper citation: miRTar (RRID:SCR_010851) Copy   

•   Source: SciCrunch Registry

http://www.cos.uni-heidelberg.de/index.php/n.ha

Software for detecting Co-Occurrence and Spatial Arrangement of Transcription Factor Binding Motifs in Genome-Wide Datasets.

Proper citation: COPS (RRID:SCR_010852) Copy   

•   Source: SciCrunch Registry

http://woldlab.caltech.edu/wiki/RNASeq#Dual-use_E-RANGE

A Python package for doing RNA-seq and ChIP-seq (hence the dual-use).

Proper citation: E-RANGE (RRID:SCR_010856) Copy   

•   Source: SciCrunch Registry

http://srs.ebi.ac.uk/srsbin/cgi-bin/wgetz?-page+srsq2+-noSession

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The EBI SRS server is a primary gateway to major databases in the field of molecular biology produced and supported at EBI as well as European public access point to the MEDLINE database provided by US National Library of Medicine (NLM). It is a reference server for latest developments in data and application integration. Features include: concept of virtual databases, integration of XML databases like the Integrated Resource of Protein Domains and Functional Sites (InterPro), Gene Ontology (GO), MEDLINE, Metabolic pathways, etc., user friendly data representation in ''Nice views'', SRSQuickSearch bookmarklets. Quick Searches allow users to make a number of searches without needing to learn how to use SRS in depth. The searches query some of the common databanks without having to go and select them explicitly and without the need to understand the SRS Query Forms. Quick Searches can be performed from either the Start page (when you first open SRS) or the SRS Quick Search page (when you are already in a project). SRS also has the ability to search for links between your current results and related information in other databanks. Additionally, it is able to analyze the results of your search using many bioinformatics analysis tools or applications. This enables you to seek out further information that may be relevant to your initial search.

Proper citation: SRS (RRID:SCR_010736) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/apps/mediawiki/vancouvershortr/index.php?title=FindPeaks

Software application that can be used for converting Eland, Maq (.map), BED or other files into WIG files and identifying areas of enrichment (ChIP-Seq analysis).

Proper citation: FindPeaks (RRID:SCR_010857) Copy   

•   Source: SciCrunch Registry

http://wanglab.pcbi.upenn.edu/coral/

A machine learning software package that can predict the precursor class of small RNAs present in a high-throughput RNA-sequencing dataset. In addition to classification, it also produces information about the features that are most important for discriminating different populations of small non-coding RNAs.

Proper citation: CoRAL - Classification of RNAs by Analysis of Length (RRID:SCR_010828) Copy   

•   Source: SciCrunch Registry

http://paed.hku.hk/uploadarea/yangwl/html/software.html

A toolkit for prioritizing SNVs and indels from next-generation sequencing data.

Proper citation: PriVar (RRID:SCR_010784) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.toronto.edu/CNVer/

A method for CNV detection that supplements the depth-of-coverage with paired-end mapping information, where matepairs mapping discordantly to the reference serve to indicate the presence of variation.

Proper citation: CNVer (RRID:SCR_010820) Copy   

•   Source: SciCrunch Registry

http://sv.gersteinlab.org/cnvnator/

An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.

Proper citation: CNVnator (RRID:SCR_010821) Copy   

•   Source: SciCrunch Registry

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

A fully automated software tool which is available for Linux to investigate associations between a diplotype group and a phenotype in linear or logistic regression.

Proper citation: Diplotyper (RRID:SCR_010789) Copy   

•   Source: SciCrunch Registry

http://bioinfo-out.curie.fr/projects/freec/tutorial.html

Prediction of copy number alterations and loss of heterozygosity using deep-sequencing data.

Proper citation: Control-FREEC (RRID:SCR_010822) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/readdepth/

This package for R can detect copy number aberrations by measuring the depth of coverage obtained by massively parallel sequencing of the genome.

Proper citation: readDepth (RRID:SCR_010824) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/vibansal/software/hapcut

A max-cut based algorithm for haplotype assembly using sequence reads from the two chromosomes of an individual.

Proper citation: HapCUT (RRID:SCR_010791) Copy   

•   Source: SciCrunch Registry

http://www.popgen.dk/software/index.php/Relate

Software providing a method that estimates the probability of sharing alleles identity by descent (IBD) across the genome and can also be used for mapping disease loci using distantly related individuals.

Proper citation: Relate (RRID:SCR_010794) Copy   

•   Source: SciCrunch Registry

http://www.nig.ac.jp/index-e.html

Institute for genetics, through National BioResource Project, collects, preserves, and provides bio-resources (strains, populations, tissues, cells, genes of animals, plants and microorganisms, and information on these materials for R&D use) that are essential for life science research.

Proper citation: National Institute of Genetics; Shizuoka; Japan (RRID:SCR_010836) Copy   

•   Source: SciCrunch Registry