| Meno: | František Václav |
|---|---|
| Priezvisko: | Man |
| Názov: | Automated Classification of the Clinical Impact of Structural Genomic Variations |
| Vedúci: | Mgr. Jaroslav Budiš, PhD. |
| Rok: | 2026 |
| Kľúčové slová: | Multiple-instance learning, MIL, miGraph, MILES, structural variants, SV, copy number variants, CNV |
| Abstrakt: | Modern biomedical technologies have enabled the detection of structural variations in a human genome. Assessing whether the detected structural variation has clinical effect has however remained a complex task, even for experienced laboratory diagnosticians. Existing computational tools often oversimplify input data used to better suite traditional machine learning methods, representing each variant as a single vector of data. As the number of affected genes differs between the variants, more flexible modelling approaches are necessary to avoid losing detailed gene-specific information. Our approach on prediction of clinical effect of CNV is based on two improvements. Firstly, we use comprehensive gene annotations to enrich the feature space. . Secondly, we shift from the traditional machine learning approaches to multiple instance learning that allows to model input data as a bags of feature instances. Such approach allows to use all gene information to better account for the varying pathogenic contributions of multiple genes within a single structural variation. |
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