How computer science can help in understanding the 3D genome architecture.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Chromosome conformation capture (3C) techniques generate large datasets on genome architecture.
• Understanding 3D genome structure is crucial for regulating cellular functions.
• Integrating spatial, temporal, genetic, and epigenetic data presents significant computational challenges.

Purpose of the Study:

• To define and explore the field of Nucleome Bioinformatics.
• To identify critical issues and challenges in analyzing 3D genome architecture data.
• To propose potential approaches for future research in Nucleome Bioinformatics.

Main Methods:

• Review of current bioinformatics tools and methods for genome architecture analysis.
• Identification of challenges in data analysis, visualization, integration, and mining.
• Discussion of high-performance computing and big data management requirements.

Main Results:

• Established Nucleome Bioinformatics as a distinct field.
• Highlighted the need for advanced computational strategies for 3D genome data.
• Identified unaddressed challenges and potential solutions for data integration and analysis.

Conclusions:

• Nucleome Bioinformatics is essential for understanding nuclear processes.
• Further development in computational methods is required to fully leverage 3C data.
• This review serves as a guide for researchers in the field.