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http://www.taverna.org.uk/

An open source and domain independent Workflow Management System ����?? a suite of tools used to design and execute scientific workflows and aid in silico experimentation. Taverna Workbench now has support for service sets, offline workflow editing, workflow validation, improved workflow run monitoring, and the pausing and canceling of workflow runs. The command line tool allows you to run workflows outside of the workbench and is available as a stand-alone download or bundled with the Taverna Workbench 2.2.0 download. The Taverna suite is written in Java and includes the Taverna Engine (used for enacting workflows) that powers both the Taverna Workbench (the desktop client application) and the Taverna Server (which allows remote execution of workflows). Taverna is also available as a Command Line Tool for a quick execution of workflows from a terminal. Taverna 2.2.0 includes * Copy/paste, shortcuts, undo/redo, drag and drop * Animated workflow diagram * Remembers added/removed services * Secure Web services support * Secure access to resources on the web * Up-to-date R support * Intermediate values during workflow runs * myExperiment integration * Excel and csv spreadsheet support * Command line tool

Proper citation: Taverna (RRID:SCR_004437) Copy   

•   Source: SciCrunch Registry

http://taylorlab.ucsf.edu/software_data.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documentedt on January 10, 2023. Software that implements babel routines for identifying unusual ribosome protected fragment counts given mRNA counts, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Babel (RRID:SCR_004307) Copy   

•   Source: SciCrunch Registry

http://www.egappreviews.org/

Initiative to develop a systematic, evidence-based process for evaluating genetic tests and other applications of genomic technology that are rapidly moving from research to use in clinical practice. A key objective of this process is to provide objective, timely, and credible information that is clearly linked to the scientific evidence on specific applications of genetic and genomic tests. The primary focus of EGAPP activities is an independent, nonfederal expert panel, the EGAPP Working Group. Other components of the EGAPP initiative include a federal interagency, the CDC staff and consultants, and an EGAPP initiative evaluation team.

Proper citation: EGAPP (RRID:SCR_004189) Copy   

•   Source: SciCrunch Registry

http://kwanlab.bio.cuhk.edu.hk/BSRD/

A repository for bacterial small regulatory RNA. They welcome you to submit new experimental validated sRNA targets.

Proper citation: BSRD (RRID:SCR_004249) Copy   

•   Source: SciCrunch Registry

http://www.cancerdiagnosis.nci.nih.gov/

National program to improve the diagnosis and assessment of cancer by moving scientific knowledge into clinical practice by coordinating and funding resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens. The Cancer Diagnosis Program is divided into four branches: Biorepository and Biospecimen Research Branch (BBRB), Diagnostic Biomarkers and Technology Branch (DBTB), Diagnostics Evaluation Branch (DEB), and the Pathology Investigation and Resources Branch (PIRB).

Proper citation: CDP (RRID:SCR_004236) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/rna-star/

Software performing alignment of high-throughput RNA-seq data. Aligns RNA-seq reads to reference genome using uncompressed suffix arrays.

Proper citation: STAR (RRID:SCR_004463) Copy   

•   Source: SciCrunch Registry

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

A web-based browser for Gene Ontology terms and annotations, which is provided by the UniProtKB-GOA group at the EBI. It is able to offer a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. The software for QuickGO is freely available under the Apache 2 license. QuickGO can supply GO term information and GO annotation data via REST web services.

Proper citation: QuickGO (RRID:SCR_004608) Copy   

•   Source: SciCrunch Registry

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

Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.

Proper citation: European Genome phenome Archive (RRID:SCR_004944) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pubmed/

Public bibliographic database that provides access to citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include fields of biomedicine and health, covering portions of life sciences, behavioral sciences, chemical sciences, and bioengineering. Provides access to additional relevant web sites and links to other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to full-text of articles at journal web sites using LinkOut.

Proper citation: PubMed (RRID:SCR_004846) Copy   

•   Source: SciCrunch Registry

http://seqanswers.com/wiki/

Wiki forum providing an extensive catalogue of manually categorized analysis tools, technologies and information about service providers, maintained by the members of the SEQanswers community. * Minimum Information about a high-throughput Sequencing Experiment * Software Hub: The place to add to, edit or browse the software database on SEQwiki. * Service Providers: Browse or edit the list of NGS service facilities. * How-to Hub: Mini reviews for the most used tools broken down by common tasks. * Developers Hub: The place to discuss the development of the SEQwiki site and its associated data. See also publishing SEQ*. * Publications: Publication about SEQwiki and selected citations.

Proper citation: SEQanswers Wiki (RRID:SCR_004810) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sra

Repository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.

Proper citation: NCBI Sequence Read Archive (SRA) (RRID:SCR_004891) Copy   

•   Source: SciCrunch Registry

http://www.arb-silva.de/aligner/

Service to align and optionally taxonomically classify your rRNA gene sequences. The results can be combined with any other sequences aligned by SINA or taken from the SILVA databases by concatenation of FASTA files or using the ARB MERGE tool. Note: Submission is currently limited to at most 1000 sequences of at most 6000 bases each. If your requirements exceed this limitation, get Opens internal link in current windowSINA for local installation.

Proper citation: SINA (RRID:SCR_005067) Copy   

•   Source: SciCrunch Registry

http://clams.jgi-psf.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 2nd, 2023. Sequence composition based classifier for metagenomic sequences. It works by capturing signatures of each sequence based on the sequence composition. Each sequence is modeled as a walk in a de Bruijn graph with underlying Markov chain properties. ClaMS captures stationary parameters of the underlying Markov chain as well as structural parameters of the underlying de Bruijn graph to form this signature. In practice, for each sequence to binned, such a signature is computed and matched to similar signatures computed for the training sets. The best match that also qualifies the normalized distance cut-off wins. In the case that the best match does not qualify this cut-off, the sequence remains un-binned.

Proper citation: Classifier for Metagenomic Sequences (RRID:SCR_004929) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.brown.edu/projects/gasv/

Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.

Proper citation: GASVPro (RRID:SCR_005259) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/prism/public/html/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy   

•   Source: SciCrunch Registry

http://www.pazar.info/

Database that unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein-DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ''boutiques'' within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PAZAR (RRID:SCR_005410) Copy   

•   Source: SciCrunch Registry

http://neurolex.org/wiki/Main_Page

A freely editable semantic wiki for community-based curation of the terms used in Neuroscience. Entries are curated and eventually incorporated into the formal NIFSTD ontology. NeuroLex also includes a Resource branch for community members to freely add neuroscience relevant resources that do not become part of NIFSTD ontology but rather make up the NIF Registry. As part of the NIF, we provide a simple search interface to many different sources of neuroscience information and data. To make this search more effective, we are constructing ontologies to help organize neuroscience concepts into category hierarchies, e.g., neuron is a cell. These categories provide the means to perform more effective searches and also to organize and understand the information that is returned. But an important adjunct to this activity is to clearly define all of the terms that we use to describe our data, e.g., anatomical terms, techniques, organism names. Because wikis provide an easy interface for communities to contribute their knowledge, we started the NeuroLex.

Proper citation: NeuroLex (RRID:SCR_005402) Copy   

•   Source: SciCrunch Registry

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

Software package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models.

Proper citation: RSeQC (RRID:SCR_005275) Copy   

•   Source: SciCrunch Registry

http://hmmer.janelia.org/

Tool for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Compared to BLAST, FASTA, and other sequence alignment and database search tools based on older scoring methodology, HMMER aims to be significantly more accurate and more able to detect remote homologs because of the strength of its underlying mathematical models. In the past, this strength came at significant computational expense, but in the new HMMER3 project, HMMER is now essentially as fast as BLAST.

Proper citation: Hmmer (RRID:SCR_005305) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.mdanderson.org/main/SpliceSeq:Overview

A Java application to investigate alternative mRNA splicing patterns in data from high-throughput mRNA sequencing studies. Sequence reads are mapped to splice graphs that unambiguously quantify the inclusion level of each exon and splice junction. The graphs are then traversed to predict the protein isoforms that are likely to result from the observed exon and splice junction reads. UniProt annotations are mapped to each protein isoform to identify potential functional impacts of alternative splicing. This tool may be used on a single RNASeq sample to identify genes with multiple spliceforms, on a pair of samples to identify differential splicing between the two, or on groups of samples to identify statistically significant group level differences in splicing patterns. SpliceSeq can be run from the install page as a java web start application to explore the sequencing data on their server or can be installed locally to analyze your own mRNA-Seq data.

Proper citation: SpliceSeq (RRID:SCR_005267) Copy   

•   Source: SciCrunch Registry