Transmembrane proteins span the lipid bilayer and are divided into two major structural classes, namely alpha helical and beta barrels. We introduce DeepTMHMM, a deep learning protein language model-based algorithm that can detect and predict the topology of both alpha helical and beta barrels proteins with unprecedented accuracy. DeepTMHMM (https://dtu.biolib.com/DeepTMHMM) scales to proteomes and covers all domains of life, which makes it ideal for metagenomics analyses.
Link to paper: https://www.biorxiv.org/content/10.1101/2022.04.08.487609v1
Professor in Genomic bioinformatics at Department of Biology, Bioinformatics, University of Copenhagen and Genomic medicine, Copenhagen University Hospital and professor in Data science and complexity at Section for Cognitive Systems, DTU Compute, Technical University of Denmark (DTU). Cofounder of raffle.ai and findzebra.com. Research interests: machine learning methodology, bioinformatics and natural language processing.