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 (30.10.2022-02.11.2022)
doi: 10.1145/3508352.3549344
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Schwarz, Tobias ; Hochberger, Christian |
| Art des Eintrags: | Bibliographie |
| Titel: | Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions |
| Sprache: | Englisch |
| Publikationsjahr: | 22 Dezember 2022 |
| Verlag: | ACM |
| Buchtitel: | ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design |
| Veranstaltungstitel: | 41st IEEE/ACM International Conference on Computer-Aided Design |
| Veranstaltungsort: | San Diego, USA |
| Veranstaltungsdatum: | 30.10.2022-02.11.2022 |
| DOI: | 10.1145/3508352.3549344 |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | genetic design automation, synthetic biology, simulated annealing, technology mapping, branch-and-bound, genetic circuits |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Rechnersysteme |
| Hinterlegungsdatum: | 10 Jan 2023 08:30 |
| Letzte Änderung: | 10 Jan 2023 15:38 |
| PPN: | 503526746 |
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