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Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions

Schwarz, Tobias ; Hochberger, Christian (2022)
Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions.
41st IEEE/ACM International Conference on Computer-Aided Design. San Diego, USA (30.10.-02.11.2022)
doi: 10.1145/3508352.3549344
Conference or Workshop Item, Bibliographie

Abstract

Synthetic Biology aims to create biological systems from scratch that do not exist in nature. An important method in this context is the engineering of DNA sequences such that cells realize Boolean functions that serve as control mechanisms in biological systems, e.g. in medical or agricultural applications. Libraries of logic gates exist as predefined gene sequences, based on the genetic mechanism of transcriptional regulation. Each individual gate is composed of different biological parts to allow for the differentiation of their output signals. Even gates of the same logic type therefore exhibit different transfer characteristics, i.e. relation from input to output signals. Thus, simulation of the whole network of genetic gates is needed to determine the performance of a genetic circuit. This makes mapping Boolean functions to these libraries much more complicated compared to EDA. Yet, optimal results are desired in the design phase due to high lab implementation costs. In this work, we identify fundamental features of the transfer characteristic of gates based on transcriptional regulation which is widely used in genetic gate technologies. Based on this, we present novel exact (Branch-and-Bound) and heuristic (Branch-and-Bound, Simulated Annealing) algorithms for the problem of technology mapping of genetic circuits and evaluate them using a prominent gate library. In contrast to state-of-the-art tools, all obtained solutions feature a (near) optimal output performance. Our exact method only explores 6.5 % and the heuristics even 0.2 % of the design space.

Item Type: Conference or Workshop Item
Erschienen: 2022
Creators: Schwarz, Tobias ; Hochberger, Christian
Type of entry: Bibliographie
Title: Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions
Language: English
Date: 22 December 2022
Publisher: ACM
Book Title: ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design
Event Title: 41st IEEE/ACM International Conference on Computer-Aided Design
Event Location: San Diego, USA
Event Dates: 30.10.-02.11.2022
DOI: 10.1145/3508352.3549344
Abstract:

Synthetic Biology aims to create biological systems from scratch that do not exist in nature. An important method in this context is the engineering of DNA sequences such that cells realize Boolean functions that serve as control mechanisms in biological systems, e.g. in medical or agricultural applications. Libraries of logic gates exist as predefined gene sequences, based on the genetic mechanism of transcriptional regulation. Each individual gate is composed of different biological parts to allow for the differentiation of their output signals. Even gates of the same logic type therefore exhibit different transfer characteristics, i.e. relation from input to output signals. Thus, simulation of the whole network of genetic gates is needed to determine the performance of a genetic circuit. This makes mapping Boolean functions to these libraries much more complicated compared to EDA. Yet, optimal results are desired in the design phase due to high lab implementation costs. In this work, we identify fundamental features of the transfer characteristic of gates based on transcriptional regulation which is widely used in genetic gate technologies. Based on this, we present novel exact (Branch-and-Bound) and heuristic (Branch-and-Bound, Simulated Annealing) algorithms for the problem of technology mapping of genetic circuits and evaluate them using a prominent gate library. In contrast to state-of-the-art tools, all obtained solutions feature a (near) optimal output performance. Our exact method only explores 6.5 % and the heuristics even 0.2 % of the design space.

Uncontrolled Keywords: genetic design automation, synthetic biology, simulated annealing, technology mapping, branch-and-bound, genetic circuits
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Computer Systems Group
Date Deposited: 10 Jan 2023 08:30
Last Modified: 10 Jan 2023 15:38
PPN: 503526746
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