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Dr. Markus Meier

Bioinformatician / Data Scientist / Research Engineer

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About Me

I love riddles, so I participated in math competitions during my school time and enjoy all kinds of games.

My job should combine my fascination for riddles with my ambition to improve the world. Science was one way to accomplish this, so I studied. I decided for Bioinformatics, since it offered the chance to target many people through the insights we learn from DNA and proteins.

However, as much as I love science it does not favor a stable life. Therefore, I am looking for a job in industry that offers challenging tasks and the opportunity to improve the lives of many.

Experience

Magazino GmbH

Research Engineer for Artificial Intelligence

  • Evaluate different multi-robot coorination approaches
  • Implementing unit/integration tests for existing ROS modules

Sulzer GmbH

Software Engineer and Data Scientist

Configuration and evaluation of Big Data pipelines.

Max-Planck Institute for Biophysical Chemistry

Postdoc Researcher in Computational Biology

Research in DNA motif discovery and continuing projects from my Ph.D.

Max-Planck Institute for Biophysical Chemistry

Scientific Assistant, Ph.D. student

  • Research in protein homology detection and de-novo protein domain discovery
  • Supervision of a master student

Gene Center at the Ludwig-Maximilians-Universität München

Scientific Assistant, Ph.D. student

  • Research in protein homology detection and de-novo protein domain discovery
  • Supervision of a bachelor student

Education

Ludwig-Maximilians-Universität München – Munich, Germany

2016

Doctor of Natural Sciences

Ludwig-Maximilians-Universität München and Technical University of Munich – Munich, Germany

2012

Master of Science

Ludwig-Maximilians-Universität München and Technical University of Munich– Munich, Germany

2011

Bachelor of Science

Projects

HHsuite

HHsuite is an open-source software package widely used in biochemistry and bioinformatics. It contains the most sensitive and fastest applications (HHsearch, HHblits) for the frequent task to search for homologous proteins. The method is based on the pairwise alignment of hidden Markov models (HMMs).

  • Moved the project from a local SVN to GitHub
  • Modernizing legacy (spaghetti) C++ code
  • Refactoring the build pipeline with cmake
  • Parallelization for HPC (Open MPI and OpenMP)
  • Support scripts for a new protein structure format (mmcif)
View Project

PEnG

Fast discovery of statistically overrepresented motifs in a set of DNA sequences. Those sequence sets can be collected from ChIP-Seq experiments, so one protein binds to all these sequences. Therefore, all these sequences should have a binding motif for this protein. However, it is not known where the motif is, what length it has and if there are multiple motifs. In this simple but fast approach we test all possible k-mers, calculate their Pvalues and optimize the k-mers first to the degenerate IUPAC alphabet and later to position specific weight matrices (PWMs). It is supposed to be a fast prefilter for BaMMmotif.

  • Based on Bayesian statistics
  • Written in C++, Python, R
View Project

Skills

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