Evidence map›Paper›PMID 36693176›Full record

ArticleACS synthetic biology2023

Context-Aware Technology Mapping in Genetic Design Automation.

Nicolai Engelmann, Tobias Schwarz, Erik Kubaczka, Christian Hochberger, Heinz Koeppl

Abstract read
In one paragraph

Article in ACS synthetic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Energy Aware Technology Mapping of Genetic Logic Circuits.bioRxiv : the preprint server for biology · 2024
    Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nicolai EngelmannDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany.
Tobias SchwarzDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany.ORCID 0000-0002-6935-8073
Erik KubaczkaDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany.
Christian HochbergerDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany.
Heinz KoepplDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic design automation (GDA) tools hold promise to speed-up circuit design in synthetic biology. Their widespread adoption is hampered by their limited predictive power, resulting in frequent deviations between the in silico and in vivo performance of a genetic circuit. Context effects, i.e., the change in overall circuit functioning, due to the intracellular environment of the host and due to cross-talk among circuits components are believed to be a major source for the aforementioned deviations. Incorporating these effects in computational models of GDA tools is challenging but is expected to boost their predictive power and hence their deployment. Using fine-grained thermodynamic models of promoter activity, we show in this work how to account for two major components of cellular context effects: (i) crosstalk due to limited specificity of used regulators and (ii) titration of circuit regulators to off-target binding sites on the host genome. We show how we can compensate the incurred increase in computational complexity through dedicated branch-and-bound techniques during the technology mapping process. Using the synthesis of several combinational logic circuits based on Cello's device library as a case study, we analyze the effect of different intensities and distributions of crosstalk on circuit performance and on the usability of a given device library.

Indexed as

AlgorithmsSynthetic BiologyAutomationGene LibraryGene Regulatory Networksbranch and boundcontext effectscrosstalkequilibrium thermodynamicsgenetic design automationtechnology mapping

Identifiers

PMID36693176
PMCPMC9942193

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.