Evidence map›Paper›PMID 26981147›Full record

ArticleComputational and mathematical methods in medicine2016

Boolean Modeling of Cellular and Molecular Pathways Involved in Influenza Infection.

Christopher S Anderson, Marta L DeDiego, David J Topham, Juilee Thakar

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 10 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

4 authors at 1 institution in 1 country.

Christopher S AndersonDepartment of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Marta L DeDiegoDepartment of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA.
David J TophamDepartment of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Juilee ThakarDepartment of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA.
University of Rochester Medical Center · US

Funding

NIAID NIH HHS HHSN272201400005CPHS HHS HHSN272201400005C
6 · The paper itself

Abstract

Systems virology integrates host-directed approaches with molecular profiling to understand viral pathogenesis. Self-contained statistical approaches that combine expression profiles of genes with the available databases defining the genes involved in the pathways (gene-sets) have allowed characterization of predictive gene-signatures associated with outcome of the influenza virus (IV) infection. However, such enrichment techniques do not take into account interactions among pathways that are responsible for the IV infection pathogenesis. We investigate dendritic cell response to seasonal H1N1 influenza A/New Caledonia/20/1999 (NC) infection and infer the Boolean logic rules underlying the interaction network of ligand induced signaling pathways and transcription factors. The model reveals several novel regulatory modes and provides insights into mechanism of cross talk between NFκB and IRF mediated signaling. Additionally, the logic rule underlying the regulation of IL2 pathway that was predicted by the Boolean model was experimentally validated. Thus, the model developed in this paper integrates pathway analysis tools with the dynamic modeling approaches to reveal the regulation between signaling pathways and transcription factors using genome-wide transcriptional profiles measured upon influenza infection.

Indexed as

AlgorithmsDatabases, FactualGene Expression ProfilingGene Regulatory NetworksHumansInfluenza A Virus, H1N1 SubtypeInfluenza, HumanInterleukin-2Models, TheoreticalNF-kappa BSignal TransductionSoftwareSystems BiologyTranscription FactorsTranscription, GeneticVirologyInterleukin-2NF-kappa BTranscription Factors

Identifiers

PMID26981147
PMCPMC4769743
OpenAlexW2259546990

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.