Control Theory for Synthetic Biology: Recent Advances in System Characterization, Control Design, and Controller Implementation for Synthetic Biology
Abstract
Living organisms are differentiated by their genetic material-millions to billions of DNA bases encoding thousands of genes. These genes are translated into a vast array of proteins, many of which have functions that are still unknown. Previously, it was believed that simply knowing the genetic sequence of an organism would be the key to unlocking all understanding. However, as DNA sequencing technology has become affordable, it has become clear that living cells are governed by complex, multilayered networks of gene regulation that cannot be deduced from sequence alone. Synthetic biology as a field might best be characterized as a learn-by-building approach, in which scientists attempt to engineer molecular pathways that do not exist in nature. In doing so, they test the limits of both natural and engineered organisms.
Additional Information
© 2018 IEEE. V. Hsiao and A. Swaminathan contributed equally to this work.Attached Files
Submitted - hsm17-ieeecsm.pdf
Files
Name | Size | Download all |
---|---|---|
md5:176c5e3d7ed6f9f9777f3ac0634d1e9d
|
8.3 MB | Preview Download |
Additional details
- Eprint ID
- 86582
- DOI
- 10.1109/MCS.2018.2810459
- Resolver ID
- CaltechAUTHORS:20180524-091716800
- Created
-
2018-05-24Created from EPrint's datestamp field
- Updated
-
2021-11-15Created from EPrint's last_modified field