PSI 2015. Tutorials.Introduction to algorithms on biosequence data

High-throughput DNA sequencing technologies generate gigabytes of sequence data in a single run of a sequencing machine. In this tutorial, we will present some modern algorithmic techniques used for processing these data. After giving a quick introduction to DNA sequencing and main computational tasks behind it, we will first focus on efficient data structures for storing these data, and especially on the so-called FM-index that recently became a very popular tool applied to biosequence analysis. We will further present several algorithms illustrating how this data structure is used in real-life applications.

BIO:

Gregory Kucherov received the PhD degree in computer science from Russian Academy of Sciences in 1988 and the habilitation degree from Henri Poincaré University in Nancy in 2000. He is currently a CNRS research director in Gaspard Monge Lab for Computer Science in Marne-la-Vallée University, France. His research interests include algorithm design and engineering, algorithmic complexity, word combinatorics, data structures, sequence analysis with applications to bioinformatics and computational biology. He (co)-authored about 40 journal publications and 50 conference papers. He supervised several software projects in bioinformatics, such as mreps, Yass or SToRM.