:: DESCRIPTION
RVboost is a novel method specific for RNA variant prioritization.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
RVboost: RNA-Seq variants prioritization using a boosting method.
Wang C, Davila JI, Baheti S, Bhagwate AV, Wang X, Kocher JP, Slager SL, Feldman AL, Novak AJ, Cerhan JR, Thompson EA, Asmann YW.
Bioinformatics. 2014 Aug 27. pii: btu577
:: DESCRIPTION
CancerDP is a web server for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine.
Gupta S, Chaudhary K, Kumar R, Gautam A, Nanda JS, Dhanda SK, Brahmachari SK, Raghava GP.
Sci Rep. 2016 Mar 31;6:23857. doi: 10.1038/srep23857.
:: DESCRIPTION
BiERapp ( BioInformatic for Rare Diseases Application) allows finding genes affected by deleterious variants that segregate along family pedigrees , case-controls or sporadic samples .
::DEVELOPER
Bioinformatics and Genomics Department at CIPF
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies.
Alemán A, Garcia-Garcia F, Salavert F, Medina I, Dopazo J.
Nucleic Acids Res. 2014 Jul;42(Web Server issue):W88-93. doi: 10.1093/nar/gku407.
:: DESCRIPTION
PupaSuite is a tool for the selection of SNPs with potential phenotypic effect to support the design of large-scale genotyping projects and the characterization of new SNPs from next generation technologies.
::DEVELOPER
Bioinformatics and Genomics Department at CIPF
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
No, Only Web Service
:: MORE INFORMATION
Citation
PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes.
Conde L, Vaquerizas JM, Dopazo H, Arbiza L, Reumers J, Rousseau F, Schymkowitz J, Dopazo J.
Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W621-5.
:: DESCRIPTION
MCDGPA is proposed to identify disease-related genes. MCDGPA is divided into three steps: module partition, genes prioritization in each disease-associated module, and rank fusion for the global ranking. When applied to the prostate cancer and breast cancer network, MCDGPA significantly improves previous algorithms in terms of cross-validation and disease-related genes prediction. In addition, the improvement is robust to the selection of gene prioritization methods when implementing prioritization in each disease-associated module and module partition algorithms when implementing network partition. In this sense MCDGPA is a general framework that allows integrating many previous gene prioritization methods and improving predictive accuracy.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Chen X, Yan GY, Liao XP (2010)
A novel candidate disease genes prioritization method based on module partition and rank fusion.
OMICS 4: 337-356.