A survey on computational approaches to identifying disease biomarkers based on molecular networks

被引：19

作者：

Qin, Guimin ^{[1
,2
]}

Zhao, Xing-Ming ^{[1
]}

机构：

[1] Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China

[2] Xidian Univ, Sch Software, Xian 710071, Peoples R China

来源：

JOURNAL OF THEORETICAL BIOLOGY | 2014年 / 362卷

基金：

中国博士后科学基金; 中国国家自然科学基金;

关键词：

Diseasome; Dysfunctional module; Dysregulated pathway; Interactome; Regulatome; PROTEIN-INTERACTION NETWORKS; GENOME-WIDE ASSOCIATION; SIGNALING PATHWAY; CANCER; GENES; PRIORITIZATION; PREDICTION; CLASSIFICATION; RECONSTRUCTION; IDENTIFICATION;

D O I：

10.1016/j.jtbi.2014.06.007

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The disease biomarkers can help make accurate diagnosis and therefore give appropriate interventions. In the past years, the accumulation of various kinds of 'omics' data, e.g. genomics and transcriptomics, makes it possible to identify disease biomarkers in a more efficient way. In particular, the molecular networks that describe the functional relationships among molecules enable the identification of disease biomarkers from a systematic perspective. In this paper, we surveyed the recent progress on the computational approaches that have been developed to identify disease biomarkers based on molecular networks. In addition, we introduced the popular resources about human interactomes and regulatomes as well as human diseasomes, whose availability makes it possible to predict the disease biomarkers with the utility of networks. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：9 / 16

页数：8

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