A transcript factor (TF) functions by binding to the recognition sites in DNA to regulate gene transcription. Without TFs, cells would not be able to effectively control the rate at which genes are expressed. Therefore, investigating binding patterns of TFs is an vital stage to understanding gene regulation.

This thesis analyzes chromatin immunoprecipitation coupled with sequencing (Chip-seq) data and gene expression data to identify TFs’ patterns in mouse embryonic stem cells. The middle point of a transcription factor binding site (TFBS) in the upstream of a gene is considered as an event in a Poisson process. Then Ripley’s K-function is applied to detect clustering and relationships between points. There are two sets of genes which are grouped through gene expression analysis by Zhou et al. (2007). This study shows that clustering and colocalization among TFs is useful to help explain and differentiate these two gene sets.