Genomic Variant Classifier Tool

Grau, I., Sengupta, D., Farid, D.M., Manderick, B., Nowe, A., Garcia Lorenzo, M.M., Daneels, D., Bonduelle, M., Croes, D. and Van Dooren , S. 2016. Genomic Variant Classifier Tool. SAI Intelligent Systems Conference 2016. London 21 Sep 2016 Springer. https://doi.org/10.1007/978-3-319-56994-9_32

TitleGenomic Variant Classifier Tool
AuthorsGrau, I., Sengupta, D., Farid, D.M., Manderick, B., Nowe, A., Garcia Lorenzo, M.M., Daneels, D., Bonduelle, M., Croes, D. and Van Dooren , S.
TypeConference paper
Abstract

The exome or genome based high throughput screening techniques are becoming a definitive criterion in the conventional clinical analysis of the genetic diseases. However, pathogenic classification of an identified variant, is still a manual and time consuming process for clinical geneticists. Thus, to facilitate the variant classification process, we have developed GeVaCT, a Java based tool that implements a classification approach based on the literature review of cardiac arrhythmia syndromes. Furthermore, the adoption of this automated knowledge engineer by the clinical geneticists will aid to build a knowledge base for the evolution of the variant classification process by use of novel machine learning approaches.

Year2016
ConferenceSAI Intelligent Systems Conference 2016
PublisherSpringer
Publication dates
Published in printAug 2016
Published online20 Aug 2017
Journal Lecture Notes in Networks and Systems book series (LNNS,volume 15)
Journal citationpp. 453-456
Book titleProceedings of SAI Intelligent Systems Conference (IntelliSys) 2016
ISBN9783319569932
9783319569949
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-56994-9_32

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