利用改进的3DMax算法重构染色体3D结构

An improved 3DMax algorithm to reconstruct three⁃dimensional structure of chromosomes

近年来,随着高通量染色体构象捕获(Hi-C)等技术的发展和高通量测序成本的降低,全基因组交互作用的数据量快速增长,交互作用图谱分辨率不断提高,促使染色体和基因组三维结构建模的研究取得了很大进展,已经提出了几种从染色体构象捕捉数据中构建单个染色体或整个基因组结构的方法。文中通过对在Hi-C数据基础上对染色体三维结构重建的相关文献进行分析,总结了重建染色体三维空间结构的经典算法3DMax的原理,并且提出了一种新的随机梯度上升算法:XNad⁃am,是Nadam优化方法的一个变体,将其应用于3DMax算法中,以便提高3DMax算法的性能,从而用于预测染色体三维结构。

In recent years,with the development of high⁃throughput chromosome conformation capture(Hi-C)technology and the reduction of high⁃throughput sequencing cost,the data volume of whole⁃genome interaction has increased rapidly,and the resolution of interaction maps keeps improving.Great progress has been made in the research of 3D structure modeling of chromosomes and genomes.Several methods have been proposed to construct chromosome structures from chromosome conformation capture data.Based on the Hi-C data,this paper analyzes the relevant literature of 3D structure reconstruction of chromosomes and summarizes the principle of 3DMax,which is a classical algorithm to construct the 3D structure of a chromosome.In this paper,a new gradient ascent optimization algorithm called XNadam is proposed,which is a variant of Nadam optimization method.When XNadam is applied to 3DMax algorithm,the performance of 3DMax algorithm can be improved,which can be used to predict the three-dimensional structure of a chromosome.