ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction

With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data are becoming increasingly available. These data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three Dimensional-Genome Reconstruction Problem (3D-GRP) seeks to take Hi-C data and produces a complete physical genome structure as it appears in the nucleus for genomic analysis. We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm (BA) which we called ChromeBat. We demonstrate on real Hi-C data that ChromeBat is capable of state-of-the-art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problemdomain. ChromeBat is an effective approach for solving the Genome Reconstruction Problem.

Automated summary

With the advancement of Next Generation Sequencing and Hi-C experiments, high quality genome-wide contact data has become more accessible. The ChromeBat method based on the Bat Algorithm is proposed to solve the Chromosome and Genome Reconstruction problem using real Hi-C data with state-of-the-art performance. ChromeBat contributes algorithmic diversity to the field of Genome Reconstruction, providing an effective approach for solving the problem.