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利用受限玻尔兹曼机识别遗传相互作用的程度——结直肠癌的研究。

Identifying the degree of genetic interactions using Restricted Boltzmann Machine-A study on colorectal cancer.

机构信息

Department of Computer Science & Engineering, Heritage Institute of Technology, Kolkata, India.

Department of Computer Science & Engineering, Netaji Subhash Engineering College, Kolkata, India.

出版信息

IET Syst Biol. 2021 Feb;15(1):26-39. doi: 10.1049/syb2.12009. Epub 2020 Dec 8.

DOI:10.1049/syb2.12009
PMID:33590963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8675802/
Abstract

The phenomenon of two or more genes affecting the expression of each other in various ways in the development of a single character of an organism is known as gene interaction. Gene interaction not only applies to normal human traits but to the diseased samples as well. Thus, an analysis of gene interaction could help us to differentiate between the normal and the diseased samples or between the two/more phases any diseased samples. At the first stage of this work we have used restricted Boltzmann machine model to find such significant interactions present in normal and/or cancer samples of every gene pairs of 20 genes of colorectal cancer data set (GDS4382) along with the weight/degree of those interactions. Later on, we are looking for those interactions present in adenoma and/or carcinoma samples of the same 20 genes of colorectal cancer data set (GDS1777). The weight/degree of those interactions represents how strong/weak an interaction is. At the end we will create a gene regulatory network with the help of those interactions, where the regulatory genes are identified by using Naïve Bayes Classifier. Experimental results are validated biologically by comparing the interactions with NCBI databases.

摘要

两个或多个基因在生物体的单一特征的发育过程中以各种方式相互影响的现象被称为基因相互作用。基因相互作用不仅适用于正常的人类特征，也适用于患病样本。因此，对基因相互作用的分析可以帮助我们区分正常和患病样本，或者区分任何患病样本的两个/更多阶段。在这项工作的第一阶段，我们使用受限玻尔兹曼机模型来发现 20 个结直肠癌数据集（GDS4382）中每对基因的正常和/或癌症样本中存在的这种显著相互作用，以及这些相互作用的权重/程度。之后，我们将在同一 20 个结直肠癌数据集（GDS1777）的腺瘤和/或癌样本中寻找这些相互作用。这些相互作用的权重/程度代表相互作用的强弱。最后，我们将借助这些相互作用创建一个基因调控网络，其中使用朴素贝叶斯分类器来识别调控基因。通过与 NCBI 数据库的比较，从生物学上验证了实验结果。

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