Thema der Dissertation:
Utilizing alignment-free methods to enable quantitative gene expression analysis of large collections of sequencing data Thema der Disputation:
Alignment free quantification of Big Data
Utilizing alignment-free methods to enable quantitative gene expression analysis of large collections of sequencing data Thema der Disputation:
Alignment free quantification of Big Data
Abstract: Due to advances in sequencing technologies, the amount of sequencing data is continuously increasing and has reached an amount that calls for new data management methods, to actually utilize the sequencing data. In the last years, a number of different indices haven been developed to simplify the data, thereby reducing the amount of space needed and enabling analysis on large collections of sequencing data. These indices are based on alignment-free methods because in this way the costly step of classical sequence analyses, the alignment, can be omitted.
In this disputation talk, an overview will be given over the different indices that have been developed, namely Reindeer, Gazelle and the Counting DBG.
In this disputation talk, an overview will be given over the different indices that have been developed, namely Reindeer, Gazelle and the Counting DBG.
Zeit & Ort
08.12.2023 | 12:00
Seminarraum 006
(Fachbereich Mathematik und Informatik, Königin-Luise-Str.24-26, 14195 Berlin)