Milí kolegové a kolegyně,

chtěli bychom vás srdečně pozvat na další přednášku semináře, která se koná zítra, tj. ve středu 4.5.2016, od 17:20 v posluchárně S5.

Karel Jalovec z ČVUT pohovoří na téma

Discriminatory analysis of sequenced read-sets

Těšíme se na vaši účast!

S pozdravem, Petr Daněček a Martin Loebl

Stránky semináře http://bioinformatika.mff.cuni.cz/seminar/

-------------- Discriminatory analysis of sequenced read-sets

Increasing amount of data obtained by the NGS technologies increases the urge of effective analysis of this data. This work presents a tool for binary classification of metagenomic samples. Metagenomic samples consist of a large amount of short DNA strings (also called reads), which belong to different organisms present in an environment from which the sample was taken. Behavior of an environment can be affected by the contamination by the organisms, which originaly do not belong in this environment. The goal of this work is to develop a classification method based on DNA superstrings that can accurately classify metagenomic samples. Classifiers obtained by this method can be used for determining whether newly obtained metagenomic samples are contaminated (positive) or clean (negative) without the need of identification of particular organisms present in the sample. We want to achieve this goal by establishing a modified sequence assembly task for finding the most discriminatory DNA superstrings. We assume that standard a approach for this kind of analysis would be to assemble all the samples and try to find the most discriminatory motifs. Both tasks are very computationally demanding. Our method should solve both these tasks simultaneously.