DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction

DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction

Abstract Background Genotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms behind this association remain elusive. With emerging multimodal data for these mechanisms, machine learning methods can be applied for pheno...

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Bibliographic Details
Main Authors: Pramod Bharadwaj Chandrashekar, Sayali Alatkar, Jiebiao Wang, Gabriel E. Hoffman, Chenfeng He, Ting Jin, Saniya Khullar, Jaroslav Bendl, John F. Fullard, Panos Roussos, Daifeng Wang
Format: Article
Language:English
Published: BMC 2023-10-01
Series:Genome Medicine
Subjects:
Deep learning
Cross-modality imputation
Auxiliary learning
Genotype–phenotype prediction
Cell-type gene regulatory networks
Schizophrenia
Online Access:https://doi.org/10.1186/s13073-023-01248-6

Internet

https://doi.org/10.1186/s13073-023-01248-6

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