Kristoffer Sahlin: Computational methods for analysis of genome and transcriptome sequencing data
Time: Wed 2020-03-11 14.00 - 15.00
Lecturer: Kristoffer Sahlin
Location: Kräftriket, house 5, room 31
In our cells, DNA and RNA hold information to answer questions about our evolution, diseases, and traits. We are now able to assay this sequence information at large scale using various high-throughput sequencing techniques. The rapid advances in sequencing technologies require parallel advances in bioinformatic algorithms. Today, fast and accurate tools are the bottleneck that stands between raw data and biological discovery. Reducing the time spent on analysis can be achieved by improving either runtime or accuracy of bioinformatic algorithms, both of which are best solved through algorithmic design.
In this talk, I will present my research on algorithms to reduce the computational bottleneck in some common bioinformatic problems encountered in genome and transcriptome sequence analysis. I will first briefly present my doctoral work on algorithms related to genomic problems such as genome assembly and structural variation detection. I will then continue to describe my recent and ongoing algorithmic work on clustering, error correction, and alignment of long-read transcriptome sequencing data.