Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases

Si Wu, Dijun Chen, Michael P. Snyder

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

With advances in high-throughput sequencing technologies, quantitative genetics approaches have provided insights into genetic basis of many complex diseases. Emerging in-depth multi-omics profiling technologies have created exciting opportunities for systematically investigating intricate interaction networks with different layers of biological molecules underlying disease etiology. Herein, we summarized two main categories of biological networks: evidence-based and statistically inferred. These different types of molecular networks complement each other at both bulk and single-cell levels. We also review three main strategies to incorporate quantitative genetics results with multi-omics data by network analysis: (a) network propagation, (b) functional module-based methods, (c) comparative/dynamic networks. These strategies not only aid in elucidating molecular mechanisms of complex diseases but can guide the search for therapeutic targets.

Original languageEnglish
Article number102101
JournalCurrent Opinion in Chemical Biology
Volume66
DOIs
StatePublished - 1 Feb 2022
Externally publishedYes

Keywords

  • Complex diseases
  • Multi-omics
  • Network analysis
  • Quantitative genetics

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry

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