Henrik Nielsen

Henrik Nielsen is an Associate Professor at the Department of Bioinformatics, Technical University of Denmark, specializing in protein sorting prediction and signal peptide analysis. His research leverages deep learning and protein language models to advance subcellular localization and secretion pathway studies.

• Department of Bioinformatics, DTU
• Focus on signal peptides, protein targeting, and computational methods

His recent work includes SignalP 6.0, DeepLoc 2.1, and SpanSeq, highlighting the integration of protein language models for multi-label localization prediction and sequence data splitting. Collaborations span projects in pathogenic eukaryotes, vaccine development, and structural bioinformatics.

Notable contributions include:

• Development of SignalP: a cornerstone tool for signal peptide cleavage prediction
• Creation of DeepLoc for membrane protein type classification
• Advancing SpanSeq to optimize deep learning model assessment

He has supervised PhD candidates in protein sorting, bioinformatics, and sequence analysis, with a focus on improving vaccine design and pathogen characterization through computational approaches.