Felix Teufel

DeepTMHMM2 predicts transmembrane protein topology and subcellular location, including re-entrant regions and interfacial helices, and identifies localization across 17 membranes.

DeepLocPro is a subcellular location predictor for prokaryotic proteins, outperforming PSORTb 3.0 on benchmark metrics using experimentally verified data.

LOL-EVE predicts promoter variant effects using a transformer model trained on mammalian promoter sequences, showing improved performance in indel prediction and haplotype analysis.

GraphPart partitions biological sequences to avoid closely related sequences in different partitions, retaining more sequences than reduction methods while maintaining homology separation quality.

MembraneFold integrates protein structure and topology prediction to visualize transmembrane proteins, offering a web server for fast and accurate analysis.

The paper uses AlphaFold-Multimer and DeepTMHMM to identify cognate receptors for secreted endogenous peptides by prioritizing interactions with high confidence metrics and filtering biologically implausible ones.

SignalP 6.0 predicts all five types of signal peptides with improved accuracy and applies to metagenomic data.