Venue: Biomedicum 1, Seminar room 1-2

Timing: 15:30 onwards

Presenter: Teemu Kivioja, Taipale Lab, Genome-Scale Biology Program

**Utilizing integer linear programming in experiment design and analysis**

Many tasks in bioinformatics involve choosing the best combination

from a vast number of different alternatives, for example the optimal

set of molecular probes from a large number of candidate probes. Many

such discrete optimization problems can be conveniently expressed in

Integer Linear Programming (ILP) or more generally Mixed Integer

Linear Programming (MILP) framework. The improvement of general ILP

solvers together with the increase in computing power has made it

possible to optimally solve many problem instances of small to medium

sizes without developing a task-specific algorithm or resorting to

heuristics. I will introduce how one can use ILP to solve experiment

design and analysis problems through simple examples taken from my own

research including molecular barcode design, CRISPR/Cas9 guide RNA

selection, and selecting a representative set of transcription factor

binding motifs.