Gunnar von Heijne

SignalP 5.0 improves signal peptide predictions using deep neural networks

Tissue-based map of the human proteome

Protein expression across human tissues Sequencing the human genome gave new insights into human biology and disease. However, the ultimate goal is to understand the dynamic exp...

Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen

SignalP 4.0: discriminating signal peptides from transmembrane regions

Improved Prediction of Signal Peptides: SignalP 3.0

Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic...

The signal peptide

A new method for predicting signal sequence cleavage sites

A new method for identifying secretory signal sequences and for predicting the site of cleavage between a signal sequence and the mature exported protein is described. The predi...

Determination of the Border between the Transmembrane and Cytoplasmic Domains of Human Integrin Subunits

In this study we have determined the position of the C-terminal end of the transmembrane domains of human integrin subunits (alpha2, alpha5, beta1, beta2) in microsomal membrane...