Identifying network-based biomarkers of complex diseases from high-throughput data.

Abstract:

:In this work, we review the main available computational methods of identifying biomarkers of complex diseases from high-throughput data. The emerging omics techniques provide powerful alternatives to measure thousands of molecules in cells in parallel manners. The generated genomic, transcriptomic, proteomic, metabolomic and phenomic data provide comprehensive molecular and cellular information for detecting critical signals served as biomarkers by classifying disease phenotypic states. Networks are often employed to organize these profiles in the identification of biomarkers to deal with complex diseases in diagnosis, prognosis and therapy as well as mechanism deciphering from systematic perspectives. Here, we summarize some representative network-based bioinformatics methods in order to highlight the importance of computational strategies in biomarker discovery.

journal_name

Biomark Med

journal_title

Biomarkers in medicine

authors

Liu ZP

doi

10.2217/bmm-2015-0035

subject

Has Abstract

pub_date

2016-06-01 00:00:00

pages

633-50

issue

6

eissn

1752-0363

issn

1752-0371

journal_volume

10

pub_type

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