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http://wiki.chasmsoftware.org/index.php/Main_Page
CHASM is a method that predicts the functional significance of somatic missense mutations observed in the genomes of cancer cells, allowing mutations to be prioritized in subsequent functional studies, based on the probability that they give the cells a selective survival advantage. SNV-Box is a database of pre-computed features of all possible amino acid substitutions at every position of the annotated human exome. Users can rapidly retrieve features for a given protein amino acid substitution for use in machine learning.
Proper citation: CHASM/SNV-Box (RRID:SCR_006445) Copy
http://cancercontrol.cancer.gov/tcrb/tturc/
A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.
Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy
Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.
Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy
http://biospecimens.cancer.gov/
The NCI Office of Biorepositories and Biospecimen Research (OBBR) was established in 2005 in recognition of the critical role that biospecimens play in cancer research. The OBBR is responsible for developing a common biorepository infrastructure that promotes resource sharing and team science, in order to facilitate multi-institutional, high throughput genomic and proteomic studies. OBBR is focused on the following objectives: * Establish biobanking as a new area of research, in order to determine the impact of various collection and processing protocols on the usefulness of biospecimens in genomic and proteomic studies * Disseminate first-generation Best Practices in order to harmonize policies and procedures of NCI-supported biorepositories * Develop future generations of biorepository best practices, based on the data generated in the biobanking research programs above * Promote professional oversight of biospecimen standards development by standards organizations * Develop new technologies for biorepository operations * Develop a biorepository accreditation program * Coordinate with the international biobanking community to harmonize policies and procedures to facilitate multi-national research
Proper citation: NCI Office of Biospecimens (RRID:SCR_007076) Copy
http://senselab.med.yale.edu/modeldb/
Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.
Proper citation: ModelDB (RRID:SCR_007271) Copy
https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view
Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.
Proper citation: Skyline (RRID:SCR_014080) Copy
Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.
Proper citation: MARRVEL (RRID:SCR_016871) Copy
https://github.com/yarden/MISO/blob/fastmiso/docs/source/sashimi.rst
Software tool for quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions.
Proper citation: Sashimiplot (RRID:SCR_016861) Copy
https://github.com/BlaisProteomics/mzStudio
Software tool for proteomics data analysis, visualization, and notebook application. Dynamic digital canvas for user driven interrogation of mass spectrometry data. Operating system Unix/Linux, Windows.
Proper citation: mzStudio (RRID:SCR_017088) Copy
https://combine-lab.github.io/salmon/
Software tool for quantifying expression of transcripts using RNA-seq data. Provides fast and bias-aware quantification of transcript expression. Transcriptome-wide quantifier to correct for fragment GC-content bias.
Proper citation: Salmon (RRID:SCR_017036) Copy
https://amp.pharm.mssm.edu/geneshot/
Software tool as search engine for ranking genes from arbitrary text queries. Enables to enter arbitrary search terms, to receive ranked lists of genes relevant to search terms. Returned ranked gene lists contain genes that were previously published in association with search terms, as well as genes predicted to be associated with terms based on data integration from multiple sources. Search results are presented with interactive visualizations.
Proper citation: Geneshot (RRID:SCR_017582) Copy
http://taylor0.biology.ucla.edu/structureHarvester/
Web based program for collating results generated by program STRUCTURE. Provides assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of number of genetic groups that best fit data. Reformats data for use in downstream programs, such as CLUMPP.It is complement for using software Structure in genetics population. Website and program for visualizing STRUCTURE output and implementing Evanno method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Structure Harvester (RRID:SCR_017636) Copy
http://www.ncbi.nlm.nih.gov/sites/GeneTests/lab
The GeneTests Web site, a publicly funded medical genetics information resource developed for physicians, other healthcare providers, and researchers, is available at no cost to all interested persons. By providing current, authoritative information on genetic testing and its use in diagnosis, management, and genetic counseling, GeneTests promotes the appropriate use of genetic services in patient care and personal decision making. At This Site: * GeneReviews: Expert-authored peer-reviewed disease descriptions * Laboratory Directory: International directory of genetic testing laboratories * Clinic Directory: International directory of genetics and prenatal diagnosis clinics * Educational Materials: Illustrated glossary, information on genetic services, PowerPoint presentations, annotated Internet resources We comply with the HONcode standard for trustworthy health information.
Proper citation: GeneTests (RRID:SCR_010725) Copy
http://proteogenomics.musc.edu/ma/musc_madb.php?page=home&act=manage
Database that is a repository for DNA microarray data generated by MUSC investigators as well as researchers in the global research community.
Proper citation: MUSC DNA Microarray Database (RRID:SCR_010977) Copy
http://oligogenome.stanford.edu/
The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.
Proper citation: OligoGenome (RRID:SCR_006025) Copy
Set of measures intended for use in large-scale genomic studies. Facilitate replication and validation across studies. Includes links to standards and resources in effort to facilitate data harmonization to legacy data. Measurement protocols that address wide range of research domains. Information about each protocol to ensure consistent data collection.Collections of protocols that add depth to Toolkit in specific areas.Tools to help investigators implement measurement protocols.
Proper citation: Phenotypes and eXposures Toolkit (RRID:SCR_006532) Copy
http://amp.pharm.mssm.edu/L1000CDS2
LINCS L1000 characteristic direction signatures search engine. Software tool to find consensus signatures that match user’s input gene lists or input signatures. Underlying dataset is LINCS L1000 small molecule expression profiles generated at Broad Institute by Connectivity Map team. Differentially expressed genes of these profiles were calculated using multivariate method called Characteristic Direction.
Proper citation: L1000 Characteristic Direction Signature Search Engine (RRID:SCR_016177) Copy
http://amp.pharm.mssm.edu/Harmonizome/
Web application that allows for searching, visualization, and prediction about genes and proteins. It contains a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from major online resources.
Proper citation: Harmonizome (RRID:SCR_016176) Copy
https://github.com/hakyimlab/PrediXcan
Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.
Proper citation: PrediXcan (RRID:SCR_016739) Copy
http://bioconductor.org/packages/release/bioc/html/ConsensusClusterPlus.html
Software written in R for determining cluster count and membership by stability evidence in unsupervised analysis. Provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset with item tracking, item consensus and cluster consensus plots.
Proper citation: ConsensusClusterPlus (RRID:SCR_016954) Copy
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