Computational methods for dissecting transcription regulatory networks

Gene expression is regulated on many levels of which transcription regulation is the most studied. Transcription factors (TF) arguably are the most integral part of transcriptional regulation; by recognizing and specifically binding to short, but degenerate, DNA sequences, TF control the transcription initiation of genes. In the mid 70s, the first mechanism of TF binding recognition was introduced which is based on simple hydrogen bonding rules. Since then numerous observations of complex TF binding site recognition has substantially altered our viewpoint of the TF binding specificity. In particular, recent studies have uncovered subtle pairwise dependencies (PD) between positions within binding sites, which disapproves the common assumption in many current computational models{ that binding positions contribute independently toward the binding affinity of a sequence. Several works already tried to incorporate PD within a framework of binding site recognition, but due to the complexity of this problem, they failed to provide a consistent and rigorous methodology. In my PhD, we have addressed PD from a computational perspective by introducing dinucleotide weight tensors (DWT), which incorporates the entire information on PD into a robust mathematical model. Among several advantages, the DWT model does not have any tunable parameters which makes it highly applicable. Finally, recent boom of high-throughput data has provided a unique window to investigate various questions regarding to binding specificity. Here, we have systematically tested the DWT model against the classical non-dependent model over a large number of human TF ChIP-seq data. The in vivo data has clearly demonstrated the role of PD in binding specificity. Remarkably, we found resulting dependency models from ChIP-seq data, outperform non-dependent models on separate in vitro data. In fact, testing over the HT-SELEX data, a high-throughput variant of the SELEX, has further corroborated the importance of PD