A Universal Approach to Identify Permissible HLA- Mismatches in HSCT: Predicted Indirectly Recognizable HLA Epitopes (2014)

Author of Publication: Kirsten A. Thus, Daniel Furst, Hanneke van Deutekom,Jorg Calis, Eric Borst, Can Kesmir, Jurgen Kuball, Joannis Mytilineos, Eric Spierings

Appeared in: Biology of Blood and Marrow Transplantation

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Matthias Niemann

Matthias Niemann

Matthias holds a Masters degree in Computer Science with a major in software engineering and a minor in Bioinformatics from Berlin University (Freie Universität). While working at Charité University Hospital in Berlin, he developed a database for kidney transplantation data and worked on various laboratory information systems and research databases. His research at Charité focused on epitope matching models and machine learning. He was instrumental in the implementation methods to increase data quality.
Since fall 2014 he focuses at PIRCHE on further improving the PIRCHE algorithm and investigating the technology's power in new domains.
Matthias Niemann