The Library
Reinforcement learning in synthetic gene circuits
Tools
Racovita, Adrian and Jaramillo, Alfonso (2020) Reinforcement learning in synthetic gene circuits. Biochemical Society Transactions, 48 (4). pp. 1637-1643. doi:10.1042/bst20200008 ISSN 0300-5127.
|
PDF
WRAP-reinforcement-learning-synthetic-gene-circuits-Racovita-2020.pdf - Accepted Version - Requires a PDF viewer. Download (866Kb) | Preview |
Official URL: http://dx.doi.org/10.1042/bst20200008
Abstract
Synthetic gene circuits allow programming in DNA the expression of a phenotype at a given environmental condition. The recent integration of memory systems with gene circuits opens the door to their adaptation to new conditions and their re-programming. This lays the foundation to emulate neuromorphic behaviour and solve complex problems similarly to artificial neural networks. Cellular products such as DNA or proteins can be used to store memory in both digital and analog formats, allowing cells to be turned into living computing devices able to record information regarding their previous states. In particular, synthetic gene circuits with memory can be engineered into living systems to allow their adaptation through reinforcement learning. The development of gene circuits able to adapt through reinforcement learning moves Sciences towards the ambitious goal: the bottom-up creation of a fully fledged living artificial intelligence.
Item Type: | Journal Article | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Subjects: | Q Science > Q Science (General) Q Science > QD Chemistry Q Science > QH Natural history |
||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||||||||
Library of Congress Subject Headings (LCSH): | Computational biology , Gene expression, Genetic regulation, Synthetic biology, Reinforcement learning , Gene regulatory networks | ||||||||||||
Journal or Publication Title: | Biochemical Society Transactions | ||||||||||||
Publisher: | Portland Press Ltd | ||||||||||||
ISSN: | 0300-5127 | ||||||||||||
Official Date: | 5 August 2020 | ||||||||||||
Dates: |
|
||||||||||||
Volume: | 48 | ||||||||||||
Number: | 4 | ||||||||||||
Page Range: | pp. 1637-1643 | ||||||||||||
DOI: | 10.1042/bst20200008 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 24 September 2020 | ||||||||||||
Date of first compliant Open Access: | 5 August 2021 | ||||||||||||
RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year