We apply conventional and deep machine learning to data analysis problems in proteomics and other high throughput data fields, utilize the flexibility and predictive strength of deep learning models as well as finding alternatives from conventional machine learning models. more

One of our main interests lies in the interpretation of quantitative profiles of many proteins simultaneously. The Perseus software is designed to achieve this by integrating computational methods from bioinformatics, statistics and machine learning. more