Christian Otto
Christian Otto
phd student
Christian Otto
Junior Research Group
Transcriptome Bioinformatics
LIFE - Leipzig Research Center
for Civilization Diseases
University Leipzig
Haertelstrasse 16-18
04107 Leipzig
E-mail:
christian@bioinf.uni-leipzig.de
Phone: +49 341 97 16 712
Background:
I studied computer science with focus on bioinformatics at the University of Leipzig, Germany. During my studies, I have been an exchange student at the MIUN University in Sundsvall for five month. I spent another four month in Jan Gorodkin's group at the KU in Copenhagen. In 2009, I completed my studies with my diploma thesis entitled 'Fast mapping using fragment chaining and indexing techniques' in Peter Stadler's group at the University of Leipzig in cooperation with Jan Gorodkin's group.
In November 2009, I worked as a PhD student in the RNomics group of Joerg Hackermueller at the Fraunhofer Institute for Cell Therapy and Immunology in Leipzig and continued being a guest researcher there. Since December 2009, I work as a PhD student in Peter Stadler's group in Leipzig and since 2010 I am also part of Steve Hoffmann's junior research group as part of the Leipzig Research Center for Civilization Diseases (LIFE).
Research interests:
Analyzing Tiling Array expression data
Despite innovations in high-throughput technologies, Tiling Arrays continue to be applied in genome-wide transcriptomics, e.g., to identify transcriptionally active coding as well as non-coding regions or to understand of dynamics in transcriptional regulation among different cellular states. In recent times, it was used in the discovery of novel long non-coding RNAs (lincRNAs) with several kilobases in length that are highly conserved and implicated in diverse biological processes.
Developing efficient algorithms for analyzing High-Throughput sequencing data
High-throughput technologies (HTS) give the great opportunity to study the transcriptional regulation and organization for the first time in a unbiased manner. However, the enormous amount of sequencing data creates several resource-demanding algorithmic problems such as error-tolerant mapping, transcript assembly to identify and quantify alternative isoforms, or statistical analyses.
Publications:
• Otto C, Hoffmann S, Gorodkin J, Stadler PF: "Fast local fragment chaining using sum-of-pair gap costs", Alg. Mol. Biol. (under review).
•Hoffmann S, Otto C, Kurtz S, Sharma CM, Khaitovich P, Vogel J, Stadler PF, Hackermueller J: "Fast mapping of short sequences with mismatches, insertions and deletions using index structures", PLoS Comput Biol (2009) vol. 5 (9) pp. e1000502