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Coding and processing of high-throughput sequencing data

TNT members involved in this project:
Dr.-Ing. Marco Munderloh
Prof. Dr.-Ing. Jörn Ostermann
Dipl.-Ing. Jan Voges

Over the past years, technological advances in sequencing (i.e., the process of reading out genomic information) have led to a faster and more cost-efficient approach to sequence individual genomes. Because of the enormous amount of sequencing data generated by high-throughput sequencing (HTS) machines, the processing, storage, and analysis of sequencing data entails novel challenges for the scientific community. Novel processes and tools have to be developed to overcome the current limitations in terms of storage space, processing speed, and many more.

Raw sequencing data generated by HTS machines passes through a great number of different analysis steps. Our goal is to develop novel algorithms to enhance the information processing "from the tissue to the hard drive".

Show all publications
  • Jan Voges, Mikel Hernaez
    Core Experiment 2 on Genomic Information Representation results LUH/Stanford/UIUC
    ISO/IEC JTC 1/SC 29/WG 11, Document Number M40224, April 2017
  • Jan Voges, Claudio Alberti, Mikel Hernaez, Tom Paridaens, James Bonfield, Paolo Ribeca, Jaime Delgado
    Unified representation of sequencing quality values
    ISO/IEC JTC 1/SC 29/WG 11, Document Number M40222, April 2017
  • Jan Voges
    Summary of Core Experiment 2 on Genomic Information Representation
    ISO/IEC JTC 1/SC 29/WG 11, Document Number M40223, April 2017