Evidence map›Paper›PMID 29335276›Full record

ArticleMolecular systems biology2018

Assigning function to natural allelic variation via dynamic modeling of gene network induction.

Magali Richard, Florent Chuffart, Hélène Duplus-Bottin, Fanny Pouyet, Martin Spichty, Etienne Fulcrand, Marianne Entrevan, Audrey Barthelaix, Michael Springer, Daniel Jost and 1 more

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2018. 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, top 84% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

11 authors at 3 institutions in 2 countries.

Magali RichardLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France magali.richard@univ-grenoble-alpes.fr daniel.jost@univ-grenoble-alpes.fr gael.yvert@ens-lyon.fr.ORCID 0000-0003-3165-3218
Florent ChuffartLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Hélène Duplus-BottinLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Fanny PouyetLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Martin SpichtyLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Etienne FulcrandLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Marianne EntrevanLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Audrey BarthelaixLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France.
Michael SpringerDepartment of Systems Biology, Harvard Medical School, Boston, MA, USA.
Daniel JostUniv. Grenoble Alpes, CNRS CHU Grenoble Alpes Grenoble INP TIMC-IMAG, Grenoble, France magali.richard@univ-grenoble-alpes.fr daniel.jost@univ-grenoble-alpes.fr gael.yvert@ens-lyon.fr.ORCID 0000-0002-9877-6864
Gaël YvertLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1 Université de Lyon, Lyon, France magali.richard@univ-grenoble-alpes.fr daniel.jost@univ-grenoble-alpes.fr gael.yvert@ens-lyon.fr.ORCID 0000-0003-1955-4786
Université Claude Bernard Lyon 1 · FRHarvard University · USInstitut polytechnique de Grenoble · FR

Funding

Determining the source of missing heritabilityR01GM120122 · NIGMS · HARVARD MEDICAL SCHOOL · PI SPRINGER, MICHAEL · 2016 to 2020
$1.7M
NIGMS NIH HHS R01 GM120122
6 · The paper itself

Abstract

More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be "personalized" according to the genotype, their variation may then reveal how DNA variants operate in the network. Here, we combined experiments and computations to visualize natural alleles of the yeast

Indexed as

Polymorphism, Single NucleotideAllelesBinding SitesGalactoseGene Expression Regulation, FungalModels, GeneticModels, MolecularProtein BindingRepressor ProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscriptional ActivationTranscription FactorsGal3 protein, S cerevisiaeGAL80 protein, S cerevisiaeGalactoseRepressor ProteinsSaccharomyces cerevisiae ProteinsTranscription Factorsgalactosepersonalized medicineSNP functionstochastic modelyeast

Identifiers

PMID29335276
PMCPMC5787706
OpenAlexW2952023529

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.