Evidence map›Paper›PMID 28087598›Full record

ArticleCancer research2017

Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells.

Rina Gendelman, Heming Xing, Olga K Mirzoeva, Preeti Sarde, Christina Curtis, Heidi S Feiler, Paul McDonagh, Joe W Gray, Iya Khalil, W Michael Korn

Open access · greenAbstract read
In one paragraph

Article in Cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
9.2field-weighted citation impact, top 2% 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

39 citing papers in PubMed, 69 citations in OpenAlex.

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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

10 authors at 6 institutions in 1 country.

Rina GendelmanDivisions of Gastroenterology and Hematology/Oncology, Department of Medicine, University of California, San Francisco, California.
Heming XingNovartis Institutes for BioMedical Research, Inc., Cambridge, Massachusetts.
Olga K MirzoevaDivisions of Gastroenterology and Hematology/Oncology, Department of Medicine, University of California, San Francisco, California.
Preeti SardePharmacyclics, Sunnyvale, California.
Christina CurtisDepartments of Medicine and Genetics, School of Medicine, Stanford University, Stanford, California.
Heidi S FeilerOregon Health and Sciences University, Portland, Oregon.
Paul McDonaghAlexion Pharmaceuticals, Lexington, Massachusetts.
Joe W GrayOregon Health and Sciences University, Portland, Oregon.
Iya KhalilGNS Healthcare, Cambridge, Massachusetts.
W Michael KornDivisions of Gastroenterology and Hematology/Oncology, Department of Medicine, University of California, San Francisco, California. Michael.Korn@ucsf.edu.
University of California, San Francisco · USOregon Health & Science University · USGNS Healthcare (United States) · USPharmacyclics (United States) · USStanford University · USSynta Pharmaceuticals (United States) · US

Funding

Systems-Based Predictions of Responses to Cancer TherapyU54CA112970 · NCI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI GRAY, JOE W. · 2004 to 2014
$27.1M
NCI NIH HHS U54 CA112970
6 · The paper itself

Abstract

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G

Indexed as

Cell CycleBayes TheoremBreast NeoplasmsCell Line, TumorCell SurvivalCyclin D1FemaleHumansIntracellular Signaling Peptides and ProteinsMitogen-Activated Protein Kinase KinasesNF-kappa BPhosphatidylinositol 3-KinasesPromoter Regions, GeneticProtein Serine-Threonine KinasesProto-Oncogene Proteins c-aktSignal TransductionCCND1 protein, humanCyclin D1Intracellular Signaling Peptides and ProteinsMitogen-Activated Protein Kinase KinasesNF-kappa BPhosphatidylinositol 3-KinasesProtein Serine-Threonine KinasesProto-Oncogene Proteins c-aktTRIB1 protein, human

Identifiers

PMID28087598
PMCPMC5410377
OpenAlexW2573268273

What OpenQuestion holds

Textmetadata
LicenceTDM
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.