基因调控网络推断研究进展

doi:10.15960/j.cnki.issn.1007-6093.2021.03.011

摘要/Abstract

摘要： 随着高通量技术的发展，越来越多的生物医学组学数据亟需处理与分析，基于运筹优化的生物信息学方法是有效解析高维生物医学数据的重要途径之一。综述了近年来在基因调控网络推断方面的研究进展。针对不同类型的转录组学数据和研究目的，分别建立了相应的基因调控网络推断方法，主要包括先验基因调控网络数据库的建立、基于条件互信息的因果网络推断、基于微分方程的动态基因调控网络推断、转录调控和转录后调控协同作用的网络推断以及基因调控网络活性评价等，并展望了基因调控网络推断的重要研究方向。

关键词: 基因调控网络推断, 因果推断, 概率图, 组合优化, 运筹与生物信息学

Abstract: With the development of high-throughput technology, more and more biomedical data need to be processed and analyzed. Bioinformatics is one of the fundamental ways to effectively analyze high-dimensional biomedical data. This paper is to provide a brief review of our recent works in gene regulatory network inference. According to different types of transcriptomic data and research purposes, the corresponding network inference methods were established, including the establishment of a priori gene regulatory network database, causal network inference based on conditional mutual information, dynamic gene regulation network inference based on differential equations, transcriptional regulation and post-transcriptional regulation inference, and the evaluation of gene regulatory network activity. At the same time, the important research directions in gene regulatory network inference are prospected.

Key words: gene regulatory network inference, causality inference, probabilistic graphical model, combinatorial optimization, operations research and bioinformatics

中图分类号:

O224

刘治平. 基因调控网络推断研究进展[J]. 运筹学学报, 2021, 25(3): 173-182.

LIU Zhiping. Some advances in gene regulatory network inference[J]. Operations Research Transactions, 2021, 25(3): 173-182.

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