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@misc{1339426, author = {Bendl, Jaroslav and Musil, Miloš and Štourač, Jan and Zendulka, Jaroslav and Damborský, Jiří and Brezovský, Jan}, keywords = {SNP effect; deleteriousness prediction; SNP prediction; mutation analysis; Mendelian diseases}, language = {eng}, institution = {MU}, organization = {MU}, title = {PredictSNP 2.0}, url = {http://loschmidt.chemi.muni.cz/predictsnp2/}, year = {2015} }
TY - ID - 1339426 AU - Bendl, Jaroslav - Musil, Miloš - Štourač, Jan - Zendulka, Jaroslav - Damborský, Jiří - Brezovský, Jan PY - 2015 TI - PredictSNP 2.0 KW - SNP effect KW - deleteriousness prediction KW - SNP prediction KW - mutation analysis KW - Mendelian diseases UR - http://loschmidt.chemi.muni.cz/predictsnp2/ L2 - http://loschmidt.chemi.muni.cz/predictsnp2/ N2 - This tool estimates the deleteriousness of single-nucleotide mutations in the context of the development of Mendelian diseases. The predictions are based on the results of existing tools: CADD, DANN, FATHMM, FunSeq2 and GWAVA. To achieve the highest possible accuracy, developed consensual functions based on category optimal decision thresholds differ according to the category of variants. These general categories are recognized: (i) regulatory, (ii) splicing, (iii) synonymous, (iv) missense and (v)nonsense variants. The evaluation on large datasets revealed a marked benefit of this approach while the web interface provides easily interpretable results for all individual tools and our consensual prediction together with the links to the relevant databases and on-line services. ER -
BENDL, Jaroslav, Miloš MUSIL, Jan ŠTOURAČ, Jaroslav ZENDULKA, Jiří DAMBORSKÝ and Jan BREZOVSKÝ. \textit{PredictSNP 2.0}. 2015.
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