Banner Banner

Prof. Dr. Martin Vingron


Max-Planck-Institut für molekulare Genetik
Abt. Bioinformatik

Ihnestraße 63-73, D-14195 Berlin

Prof. Dr. Martin Vingron

Prof. Dr. Martin Vingron

Fellow | BIFOLD

Honorarprofessor | Freie Universität Berlin, Fachbereich Mathematik und Informatik

Director of  Computational Molecular Biology Department | Max Planck Institute for Molecular Genetics

Martin Vingron studied mathematics in Vienna, Austria, and received his PhD in mathematics in 1991 from Heidelberg University for work done at EMBL, the European Molecular Biology Laboratory. After two postdocs in Los Angeles and Bonn, respectively, he became head of the Theoretical Bioinformatics Division at the German Cancer Research Center (DKFZ). In 2000 he became a Scientific Member of Max Planck Society and moved to the MPIMG in Berlin. Vingron was awarded the Max Planck Research Prize in 2004. He is a member of the German Academy of Sciences Leopoldina and an Elected Fellow of the International Society for Computational Biology. He holds an adjunct professorship (“Honorarprofessur”) at Freie Universität Berlin.

Martin Vingron works on various aspects of computational molecular biology. He develops and applies both algorithmic and statistical techniques to the questions of molecular biology and of genome research. After several years in the fields of biological sequence analysis, sequence comparison, and molecular evolution, he turned to questions of data analysis in functional genomics, in particular gene expression data. Currently Vingron works on employing sequence analysis and functional genomics for the purpose of studying gene regulation. The emphasis is on the interplay of epigenetic modifications and gene regulation.

2004 Max Planck Forschungspreis

  • Computational molecular biology
  • Biological sequence analysis
  • Sequence comparison
  • Phylogeny reconstruction
  • Genome analysis
  • Microarray data analysis
  • Transcriptional regulation
  • Functional genomics
  • Development of algorithms and statistical methods for molecular biology

  • ISCB International Society for Computational Biology
  • ACM
  • Royal Statistical Society