FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi.

ABSTRACT: mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE-a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on thre

SUBMITTER: Nambiar A 

PROVIDER: S-EPMC10653424 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature