Identification of aberrant pathways and network activities from high-throughput data

被引：18

作者：

Wang, Jinlian ^{[1
]}

Zhang, Yuji ^{[2
]}

Marian, Catalin ^{[3
,4
]}

Ressom, Habtom W. ^{[1
]}

机构：

[1] Georgetown Univ, Lombardi Comprehens Canc Ctr, Washington, DC 20057 USA

[2] Mayo Coll Med, Dept Hlth Sci Res, Div Biomed Stat & Informat, Rochester, MN 55905 USA

[3] Ohio State Univ, Ctr Comprehens Canc, Columbus, OH 43210 USA

[4] Ohio State Univ, Dept Internal Med, Columbus, OH 43210 USA

来源：

BRIEFINGS IN BIOINFORMATICS | 2012年 / 13卷 / 04期

关键词：

pathways; biological networks; biomarker discovery; omics studies; systems biology; PROTEIN-INTERACTION NETWORKS; BREAST-CANCER; METABOLIC NETWORKS; SYSTEMS BIOLOGY; O-GLCNACYLATION; CROSS-TALK; REVEALS; MODELS; RECONSTRUCTION; INFERENCE;

D O I：

10.1093/bib/bbs001

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Many complex diseases such as cancer are associated with changes in biological pathways and molecular networks rather than being caused by single gene alterations. A major challenge in the diagnosis and treatment of such diseases is to identify characteristic aberrancies in the biological pathways and molecular network activities and elucidate their relationship to the disease. This review presents recent progress in using high-throughput biological assays to decipher aberrant pathways and network activities. In particular, this review provides specific examples in which high-throughput data have been applied to identify relationships between diseases and aberrant pathways and network activities. The achievements in this field have been remarkable, but many challenges have yet to be addressed.

引用

页码：406 / 419

页数：14

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