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. 2012 Jul;13(4):430-45.
doi: 10.1093/bib/bbs026.

Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities

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Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities

Chang F Quo et al. Brief Bioinform. 2012 Jul.

Abstract

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.

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Figures

Figure 1
Figure 1
Integrated pipeline for reverse engineering biomolecular systems (REBMS) using high-throughput –omic data that combines data mining, modeling and simulation and testing and validation
Figure 2
Figure 2
Dual role of synthetic biology in reverse engineering biomolecular systems (REBMS): (left) to test and validate models as a result of upstream mining and modeling, i.e. as the third step in a conventional workflow and (right) to create biomolecular components, devices and systems for analysis-by-synthesis, i.e. synthetic biology is the driver for REBMS

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