3D Chromosome and Genome Structure Modeling and Visualization

Fall 2015 – present

Keywords: Hi-C; Machine learning; Deep Learning; Optimization algorithm; Bioinformatics; 3D chromosome structure; 3D genome; Chromosome conformation capture
Source: Trieu, T., & Cheng, J. (2017). 3D genome structure modeling by Lorentzian objective function. Nucleic acids research, 45(3), 1049-1058


The development of chromosomal conformation capture techniques, particularly, the Hi-C technique, has made the analysis and study of the spatial conformation of a genome an important topic in bioinformatics and computational biology. Aided by high-throughput next generation sequencing techniques, the Hi-C technology can generate read pairs that indicate the chromosomal locations within spatial proximity and large-scale intra- and inter-chromosomal interaction occuring within a genome (Lieberman-Aiden et al, 2009). This data can be used to reconstruct 3D structures of chromosomes that can be used to study DNA replication, gene regulation, genome interaction, genome folding, and genome function. This data is called the Hi-C data. Generally, before Hi-C data are used for model construction, they are converted to a matrix form known as a contact matrix or a contact map is a N * N matrix, extracted from a Hi-C data, showing the number of interactions between chromosomal regions. The size of the matrix (N) is the number of equal-size regions of a chromosome. The length of equal-size regions (e.g. 1 Mb base pair) is called resolution. Each entry in the matrix contains a count of read pairs that connect two corresponding chromosome regions in a Hi-C experiment. Therefore, the chromosome contact matrix represents all the observed interactions between the regions (or bins) in a chromosome.

Our focus on this project area can be subdivided into two:

3D Chromosome and Genome Structure Modeling:
This work focuses on developing novel and high-performing prediction tools and algorithms for advanced chromosome and genome 3D structure reconstruction; and the development of more robust tools that yields superior reconstruction accuracy for different Hi-C resolution dataset.

3D Chromosome and Genome Structure Visualization:
As important as 3D construction is, equally important is the visualization of the constructed 3D structure and the presentation of the relationships existing within them. Highlighting the structural relationships present within the genome structure is important for explaining otherwise unobservable functions when examining DNA sequence information alone. This work focuses on developing novel and high-performing tools and software for advanced visualization of chromosome and genome 3D structures


All our algorithms are made public, open-source, and freely accessible to all through our GitHub repository

This work is supported by:
NSF CISE Research Initiation Initiative (CRII) Grant Award | Award Dates: 2022 to Present
UCCS Committee on Research and Creative Works (CRCW) Seed Grant Award | Award Dates: 2020-2022
(719) 255-3004
ooluwada [at] uccs [dot] edu
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