Predicting Fitness-Related Traits Using Gene Expression and Machine Learning.

ABSTRACT: Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance of gene products expressed in a tissue can be considered a phenotype intermediate to the genes and genomic regulatory elements themselves and more traditionally measured macroscopic phenotypic traits such as flowering time, size, or growth. The high dimensionality, low sample size nature of transcriptomic sequence data is a double-edged sword, however, as it provides abundant information but makes traditional statistics difficult. Machine learning (ML) has many features which handle high-dimensional data well and is thus useful in genetic sequen

SUBMITTER: Henry GA 

PROVIDER: S-EPMC11844753 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature