A cross-level information transmission network for hierarchical omics data integration and phenotype prediction from a new genotype.

ABSTRACT:

Motivation

An unsolved fundamental problem in biology is to predict phenotypes from a new genotype under environmental perturbations. The emergence of multiple omics data provides new opportunities but imposes great challenges in the predictive modeling of genotype-phenotype associations. Firstly, the high-dimensionality of genomics data and the lack of coherent labeled data often make the existing supervised learning techniques less successful. Secondly, it is challenging to integrate heterogeneous omics data from different resources. Finally, few works have explicitly modeled the information transmission from DNA to phenotype, which involves multiple intermediate molecular types. Higher-level features (e.g. gene expression) usually have stronger discriminative and interpretable p

SUBMITTER: He D 

PROVIDER: S-EPMC8696111 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature