Design and Implementation of Chromatin Structure Analysis Service Using Hi-C Data Similarity Assessment Method

The aim of this work is to present a service for analyzing chromatin structure using the Hi-C data similarity assessment method. The development of this service is motivated by the challenges faced by researchers in interpreting complex Hi-C datasets, which are crucial for understanding the three-dimensional organization of chromatin and its impact on gene expression and cellular functions. This service contributes to a deeper understanding of chromatin dynamics and interactions. By providing a convenient platform for analyzing chromatin structure, the service aims to empower the research community to unravel the mechanisms of gene expression regulation. Future enhancements will focus on integrating additional features such as comparative analysis of different cell types. Keywords: Bioinformatics, Chromatin, Hi-C analysis, Three-dimensional genome structure, Hi-C data interpretation, Python, Cooler, PyQT.