GOPHER, an HPC framework for large scale graph exploration and inference

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hdl:2117/331891
Document typeConference report
Defense date2020
PublisherSpringer
Rights accessOpen Access
Abstract
Biological ontologies, such as the Human Phenotype Ontology (HPO) and the Gene Ontology (GO), are extensively used in biomedical research to investigate the complex relationship that exists between the phenome and the genome. The interpretation of the encoded information requires methods that efficiently interoperate between multiple ontologies providing molecular details of disease-related features. To this aim, we present GenOtype PHenotype ExplOrer (GOPHER), a framework to infer associations between HPO and GO terms harnessing machine learning and large-scale parallelism and scalability in High-Performance Computing. The method enables to map genotypic features to phenotypic features thus providing a valid tool for bridging functional and pathological annotations. GOPHER can improve the interpretation of molecular processes involved in pathological conditions, displaying a vast range of applications in biomedicine.
CitationJosep, M. [et al.]. GOPHER, an HPC framework for large scale graph exploration and inference. A: International Conference on High Performance Computing. "High Performance Computing: ISC High Performance 2020 International Workshops: Frankfurt, Germany, June 21–25, 2020: revised selected papers". Berlín: Springer, 2020, p. 211-222. ISBN 978-3-030-59851-8. DOI 10.1007/978-3-030-59851-8_13.
ISBN978-3-030-59851-8
Publisher versionhttps://link.springer.com/chapter/10.1007/978-3-030-59851-8_13
Collections
- Departament de Ciències de la Computació - Ponències/Comunicacions de congressos [1.118]
- Computer Sciences - Ponències/Comunicacions de congressos [347]
- KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic - Ponències/Comunicacions de congressos [98]
- CAP - Grup de Computació d'Altes Prestacions - Ponències/Comunicacions de congressos [686]
- Departament d'Arquitectura de Computadors - Ponències/Comunicacions de congressos [1.612]
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