Machine learning and combinatorial optimization to detect gene-gene interactions in genome-wide real data: looking through the prism of four methods and two protocols - Archive ouverte HAL
Chapitre D'ouvrage Année : 2020

Machine learning and combinatorial optimization to detect gene-gene interactions in genome-wide real data: looking through the prism of four methods and two protocols

Hugo Boisaubert
  • Fonction : Auteur
  • PersonId : 1041832
Laboratoire des Sciences du Numérique de Nantes
Christine Sinoquet
Laboratoire des Sciences du Numérique de Nantes
CV

Domaines

Apprentissage [cs.LG] Algorithme et structure de données [cs.DS] Recherche opérationnelle [math.OC] Bio-informatique [q-bio.QM]

Christine Sinoquet  : Connectez-vous pour contacter le contributeur

https://hal.science/hal-02455132

Soumis le : samedi 25 janvier 2020-13:48:45

Dernière modification le : jeudi 21 novembre 2024-18:14:02

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hal-02455132 , version 1 (25-01-2020)

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  • HAL Id : hal-02455132 , version 1

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Hugo Boisaubert, Christine Sinoquet. Machine learning and combinatorial optimization to detect gene-gene interactions in genome-wide real data: looking through the prism of four methods and two protocols. Biomedical Engineering Systems and Technologies, 12th International Joint Conference, BIOSTEC2019, Czech Republic, Prague, 22-24 february, Extended Selected Papers, Communication in Computer and Information Science, A. Fred and H. Gamboa (eds.), Springer, 29 pages, In press. ⟨hal-02455132⟩

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