NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

ABSTRACT: Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the Neuro

SUBMITTER: Wei Z 

PROVIDER: S-EPMC10104575 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature