Evidence map›Paper›PMID 25965584›Full record

ArticlePloS one2015

Effect of noise in intelligent cellular decision making.

Russell Bates, Oleg Blyuss, Ahmed Alsaedi, Alexey Zaikin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Russell BatesDepartment of Mathematics, University College London, London, UK.
Oleg BlyussInstitute for Women's Health, University College London, London, UK.
Ahmed AlsaediDepartment of Mathematics, King AbdulAziz University, Jeddah, Saudi Arabia.
Alexey ZaikinDepartment of Mathematics, University College London, London, UK; Institute for Women's Health, University College London, London, UK; Lobachevsky State University of Nizhniy Novgorod, Nizhniy Novgorod, Russia.

Funding

Cancer Research UK 12677
6 · The paper itself

Abstract

Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.

Indexed as

AlgorithmsArtificial IntelligenceSignal-To-Noise Ratio

Identifiers

PMID25965584
PMCPMC4429125

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.