HIGHLIGHTS
- who: PROCEEDINGS and colleagues from the (UNIVERSITY) have published the research work: Predicting cancer-associated germline variations in proteins, in the Journal: (JOURNAL)
- what: The authors implement a new method based on Support Vector Machines that takes as input the protein variant and the protein function as described by its associated Gene Ontology terms. The authors trained and tested Support Vector Machines (SVMs) with several kernel functions and here the authors report the results obtained with the best performing one: Radial Basis Functions (RBFs). From the analysis described above the authors can conclude that the . . .
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