Title | Genomic Variant Classifier Tool |
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Authors | 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. |
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Type | Conference paper |
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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. |
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Year | 2016 |
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Conference | SAI Intelligent Systems Conference 2016 |
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Publisher | Springer |
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Publication dates |
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Published in print | Aug 2016 |
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Published online | 20 Aug 2017 |
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Journal | Lecture Notes in Networks and Systems book series (LNNS,volume 15) |
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Journal citation | pp. 453-456 |
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ISSN | 2367-3389 |
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| 2367-3370 |
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Book title | Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 |
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ISBN | 9783319569932 |
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| 9783319569949 |
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Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-319-56994-9_32 |
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