Identification of Gene Networks: An Approach Based on Mathematical Modeling
Abstract
The reverse engineering of transcriptional regulatory networks is one of the grand challenges of systems biology. In this project, we sought to develop a mathematical theory to determine a minimal set of experimental measurements needed to reverse engineer a transcriptional regulatory network. We developed a theoretically near-optimal reverse engineering method called the sensitivity method. We showed through computational experiments that, compared to predominant existing approaches, the sensitivity method leads to vastly reduced experimental cost and greater accuracy. On a 100-gene network, the experimental cost is reduced by an order of magnitude, with the level of reduction increasing as the size of the network increases. We applied the sensitivity method to a five-gene subnetwork of Escherichia coli and obtained promising preliminary experimental results.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 21, 2014
- Accession Number
- ADA613602
Entities
People
- Desmond S. Lun
Organizations
- Rutgers University–Camden