Random forest as a tumour genetic marker extractor
| Autor: | Pérez Arnal, Raquel Leandra|||0000-0002-0041-8146, Garcia Gasulla, Dario|||0000-0001-6732-5641, Torrents Rodas, David, Pares, Ferran, Cortés García, Claudio Ulises|||0000-0003-0192-3096, Labarta Mancho, Jesús José|||0000-0002-7489-4727, Ayguadé Parra, Eduard|||0000-0002-5146-103X |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | Finding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development. In this paper, we explore a recently released dataset of chromosome rearrangements in 2,586 cancer patients, where different sorts of alterations have been detected. Using a Random Forest classifier, we evaluate the relevance of several features (some directly available in the original data, some engineered by us) related to chromosome rearrangements. This evaluation results in a set of potential tumour genetic markers, some of which are validated in the bibliography, while others are potentially novel. This work is partially supported by the Joint Study Agreement no. W156463 under the IBM/BSC Deep Learning Center agreement, by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, and by the Generalitat de Catalunya (contracts 2017-SGR-1414). |
| Databáze: | OpenAIRE |
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