Evidence map›Paper›PMID 36970395›Full record

ArticleEngineering biology2020

Dynamical model fitting to a synthetic positive feedback circuit in

Jure Tica, Tong Zhu, Mark Isalan

Open access · goldAbstract read
In one paragraph

Article in Engineering biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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

3 authors at 1 institution in 1 country.

Jure TicaDepartment of Life Sciences Imperial College London London SW7 2AZ UK.ORCID https://orcid.org/0000-0002-3989-3577
Tong ZhuDepartment of Life Sciences Imperial College London London SW7 2AZ UK.
Mark IsalanDepartment of Life Sciences Imperial College London London SW7 2AZ UK.
Imperial College London · GB

Funding

Wellcome Trust 102944/Z/13/Z
6 · The paper itself

Abstract

Applying the principles of engineering to Synthetic Biology relies on the development of robust and modular genetic components, as well as underlying quantitative dynamical models that closely predict their behaviour. This study looks at a simple positive feedback circuit built by placing filamentous phage secretin pIV under a phage shock promoter. A single-equation ordinary differential equation model is developed to closely replicate the behaviour of the circuit, and its response to inhibition by TetR. A stepwise approach is employed to fit the model's parameters to time-series data for the circuit. This approach allows the dissection of the role of different parameters and leads to the identification of dependencies and redundancies between parameters. The developed genetic circuit and associated model may be used as a building block for larger circuits with more complex dynamics, which require tight quantitative control or tuning.

Indexed as

biology computingcircuit feedbackcomplex dynamicsdifferential equationsdynamical model fittingE. colifeedbackgeneticsmodular genetic componentsordinary differential equation modelphage shock promoterpositive feedback circuitsynthetic biologysynthetic positive feedback circuittime seriestime‐series data

Identifiers

PMID36970395
PMCPMC9996705
OpenAlexW3029230275

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.