Machine Learning in Genome-Wide Association Studies

• Autore: Hu Ting
• Pubblicazione: Frontiers Media SA, 2020
• Descrizione fisica: 1 electronic resource (74 p.)
• Soggetto topico: Science: general issues; Medical genetics
• Soggetto non controllato: GWAS—genome-wide association study; machine learning; complex diseases; gene-gene interaction; epistasis
• Persona (resp. second.): UrbanowiczRyan; DarabosChristian; HuTing
• Sommario/riassunto: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
• Titolo autorizzato: Machine Learning in Genome-Wide Association Studies
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557760703321
• Lo trovi qui: Univ. Federico II