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Andreas Keller

keller

Prof. Andreas Keller - Chair of Clinical Bioinformatics, Saarland University, Bad Homburg

Prof. Dr. Andreas Keller is heading the Chair for Clinical Bioinformatics at the medical faculty of Saarland University and member of the Center for Bioinformatics. Before becoming full professor in 2013 at the age of 31, he worked for the Heidelberg based biomarker company febit biomed, now comprehensive biomarker center, (2009-­‐2011) and lead the diagnostic innovation group at Siemens Healthcare (2011-­‐2013).

Keller holds a Ph.D. in computational biology and qualified as professor in human genetics at Saarland University Hospital. In his scientific career, he published over 100 peer reviewed journal articles. Selected publications were accepted in high-­‐rank journals such as Nature Biotechnology or Nature Methods. Besides scientific publications, Keller (co-­‐)filed 46 patents in the area of biomarker research. Based on his experience he recently published together with Prof. Eckart Meese a book entitled “Nucleic Acid for Molecular Diagnostic”.

Current research areas of Prof. Keller include the discovery and validation of multiplex biomarker signatures, genetic tests for improved therapy selection for multi drug resistant bacteria and complex systems biology approaches. Since the Chair for Clinical Bioinformatics has a highly translational character, Keller works closely together with different companies to bring the research from bench to bedside. Besides acquiring research funding, he also works as consultant for different diagnostic and therapeutic companies.

Project: Improved diagnostic of in-vitro-fertilization using miRNome and microvesicles from early stage embryos

We want to improve the understanding of molecular processes related to human infertility. Specifically, we aim at capturing the information flow between the oocyte and the women retrieving the early embryonic stages by monitoring the amount of microvesicles including exosomes. This information is then combined with molecular profiles obtained from culture media prior to implantation. As information carriers we focus on microRNAs that partially derive from exosomes, other microvesicles and cells. miRNAs are small RNA molecules of around 20 nucleotides that are transcribed from the genome but are not translated to proteins and thus belong to the class of non-coding RNAs. Using microarray technology we will profile the repertoire of over 2,000 human miRNAs in the samples. Then, we correlate the observed molecular patterns with information derived from the microvesicle distribution and with outcomes of the pregnancy, such as abort rates and live birth rates. Beyond the classical statistical analysis we will also perform a systems biology modeling of the information flow based on miRNAs. One objective of our project is to identify miRNAs as biomarkers to predict embryo quality and to contribute to an optimized embryo transferred leading to successful pregnancy.

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