마틴 스타이네거

조교수

마틴 스타이네거 Martin Steinegger

마틴 스타이네거
연구분야
생물정보학
Our group develops novel computational methods to analysis large DNA/RNA sequence set:
- Sequence search, clustering and assembly
- Pathogens detection
- Metagenomics analysis.
 
- Protein function and structure prediction
학력/경력
학력
  • - 2014 - 2018 Ph.D. in Computer Science at the Technical University Munich
  • - 2013 - 2014 Master of Science in Computer Science at the Ludwig Maximilian University
  • - 2010 - 2013 Bachelor of Science in Bioinformatics at TU Munich / Ludwig Maximilian University
경력
  • - since 2020 Assistant Professor, School of Biological Sciences, Seoul National University
  • - 2018 - 2020 Post-doctoral Researcher, Johns Hopkins University School of Medicine
  • - 2014 - 2018 Research Fellow, Max-Planck Institute for Biophysical Chemistry
주요논문
  1. Steinegger, M., Milot Mirdita, and Söding, J. (2019) Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold Nature Methods, 16, 603–606, doi: 10.1038/s41592-019-0437-4
  2. Steinegger, M., and Söding, J. (2018) Clustering huge protein sequence sets in linear time Nature Communications doi: 10.1038/s41467-018-04964-5
  3. Steinegger, M., and Söding, J. (2017) MMseqs2: Sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, 35, 1026–1028, doi: 10.1038/nbt.3988
  4. Mirdita, M.#, von den Driesch#, L., Galiez, G., Martin, M., Söding, J.∗, and Steinegger, M.∗ (2017) Uniclust databases of clustered and deeply annotated protein sequences and alignments. Nucleic Acids Research, 45, D170–D176, doi: 10.1093/nar/gkw1081. . (#Equal contributions.) (∗Corresponding authors.)