This is an annual data challenge for the course "machine learning with kernel methods'' for the master programs MVA, MASH and MSV.
The purpose here is to predict whether a DNA sequence region is binding site to a specific transcription factor.
Transcription factors (TFs) are regulatory proteins that bind specific sequence motifs in the genome to activate or repress transcription of target genes.
Genome-wide protein-DNA binding maps can be profiled using some experimental techniques and thus all genomics can be classified into two classes for a TF of interest: bound or unbound.
In this challenge, we work with three datasets corresponding to three different TFs.