Evidence map›Paper›PMID 25579192›Full record

ReviewNew biotechnology2015

Designer cell signal processing circuits for biotechnology.

Robert W Bradley, Baojun Wang

Abstract readReview
In one paragraph

Review in New biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. GenoMine: a CRISPR-Cas9-based kill switch for biocontainment ofFrontiers in bioengineering and biotechnology · 2024
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Synthetic Biology Enables Programmable Cell-Based Biosensors.Chemphyschem : a European journal of chemical physics and physical chemistry · 2020
    Review
  8. Article
  9. Article
  10. 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

2 authors.

Robert W BradleyDepartment of Life Sciences, Faculty of Natural Sciences, Imperial College London, London SW7 2AZ, UK; Centre for Synthetic and Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK.
Baojun WangCentre for Synthetic and Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK. Electronic address: Baojun.Wang@ed.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/K016288/1
6 · The paper itself

Abstract

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field.

Indexed as

AnimalsBiotechnologyHumansMetabolic EngineeringMetabolic Flux AnalysisProteomeSignal TransductionSynthetic BiologyProteome

Identifiers

PMID25579192
PMCPMC4571992

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.