Improved Modeling of RNA-binding Protein Motifs in an Interpretable Neural Model of RNA Splicing

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2024 Jan 16

PMID 38229106

Authors

Kavi Gupta

Chenxi Yang

Kayla McCue

Osbert Bastani

Phillip A Sharp

Christopher B Burge

Armando Solar-Lezama

Affiliations

Soon will be listed here.

Abstract

Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions. Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity models for 79 human RBPs and the annotated human genome to produce improved models of RBP binding and activity. Binding and activity are modeled by separate Motif and Aggregator components that can be mixed and matched, enforcing sparsity to improve interpretability. Training a new Adjusted Motif (AM) architecture on the splicing task not only yields better splicing predictions but also improves prediction of RBP-binding sites in vivo and of splicing activity, assessed using independent data.

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