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Updated: May 6, 2026

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Published on: May 6, 2010

3D chromosome modeling with semi-definite programming and Hi-C data.

Zhizhuo Zhang¹, Guoliang Li, Kim-Chuan Toh

¹1 School of Computing, National University of Singapore , Singapore, Singapore .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|November 8, 2013

Summary

Scientists can now model the 3D genome structure using Hi-C data. ChromSDE, a new computational method, accurately reconstructs these structures and reveals biological insights.

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Area of Science:

Genomics
Computational Biology
Structural Biology

Background:

Genomes were historically viewed as linear, but chromosome conformation capture (3C) technologies like Hi-C reveal genome-wide loci contact frequencies.
Hi-C data indicates that distant loci can interact, suggesting genomes form three-dimensional (3D) structures within the nucleus.

Purpose of the Study:

To computationally model the 3D chromosomal structure from Hi-C data.
To develop a robust and accurate method for 3D genome structure reconstruction.

Main Methods:

Developed ChromSDE, a deterministic method using semi-definite programming to fit observed Hi-C data.
Employed golden section search to determine the contact frequency to spatial distance conversion parameter.
Introduced a consensus index to assess data for single or mixed structural populations.

Main Results:

ChromSDE guarantees correct structure recovery in noise-free scenarios.
Demonstrated theoretically and empirically that the contact frequency to spatial distance conversion parameter varies with resolution.
Showed ChromSDE significantly outperforms existing methods in accuracy and robustness using simulation and real Hi-C data.

Conclusions:

ChromSDE provides a powerful computational tool for modeling 3D genome structures from Hi-C data.
The consensus index aids in interpreting the nature of the genomic structural ensemble.
Predicted 3D structures can lead to novel biological discoveries.