Hiv-haplotype inference using a constraint-based dirichlet process mixture model

 Joint ICS Forum and HIIT Seminar Otaniemi talk:

          Hiv-haplotype inference using a constraint-based
                  dirichlet process mixture model

                         Prof. Volker Roth
                   Universität Basel, Switzerland

Abstract:

The recent introduction of the Deep Sequencing technology has led to a
drastic increase in sequenced data, but the limited length of these
sequenced reads and non-negligible sequencing errors have also opened
new statistical challenges in analyzing the data.  This work aims at
analyzing deep sequencing data obtained in a single run from
genetically diverse samples, in particular from intra-host HIV
populations: HIV exists in a single infected patient as quasispecies,
a population of evolutionarily related haplotypes.  We present a
constraint-based Dirichlet process mixture model for identifying (an a
priori unknown number of) these haplotypes in a sample and thereby
quantifying the observed genetic diversity, which defines an important
step in administering personalized medication.

Date:  Thursday, 16 December, 2010
Time:  12:15--13:00
Venue: Lecture hall T3, Computer Science building

Welcome!