Feature selection methods for mining bio-informatics data

Bontempi G, Haibe-Kains B

The use of data mining techniques in bioinformatics is continuously confronted with the problem of managing datasets where the number of features is much larger than the number of samples (high feature-to-sample ratio datasets). The talk will first discuss some examples (from inference of regulatory networks to discrimination in cancer classification) and then will focus on some issues to be be taken into account for effectively dealing with this type of data.