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Cited by 325

The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.

Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data

Open access
Yan, Jingwen, Risacher, Shannon L, Shen, Li, Saykin, Andrew J.·2017·Briefings in Bioinformatics

Abstract

In the past decade, significant progress has been made in complex disease research across multiple omics layers from genome, transcriptome and proteome to metabolome. There is an increasing awareness of the importance of biological interconnections, and much success has been achieved using systems biology approaches. However, because of the typical focus on one single omics layer at a time, existing systems biology findings explain only a modest portion of complex disease. Recent advances in multi-omics data collection and sharing present us new opportunities for studying complex diseases in a more comprehensive fashion, and yet simultaneously create new challenges considering the unprecedented data dimensionality and diversity. Here, our goal is to review extant and emerging network approaches that can be applied across multiple biological layers to facilitate a more comprehensive and integrative multilayered omics analysis of complex diseases.

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Crossref · 10.1093/bib/bbx066

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Metadata

Authors
Yan, J., Risacher, S. L., Shen, L., & Saykin, A. J.
Venue
Briefings in Bioinformatics
Published
2017-06-30
Volume
19
Issue
6
Pages
1370-1381
ISSN
  • 1467-5463 (ISSN-L)
  • 1477-4054
OpenAlex
W2733047156
Cited by
325
References
109
FWCI
7.47
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data. https://app.cochat.ai/papers/10.1093/bib/bbx066
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Yan, J., Risacher, S. L., Shen, L., & Saykin, A. J. (2017). Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbx066

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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