Evidence map›Paper›PMID 29163636›Full record

ArticleFrontiers in genetics2017

A Pipeline for High-Throughput Concentration Response Modeling of Gene Expression for Toxicogenomics.

John S House, Fabian A Grimm, Dereje D Jima, Yi-Hui Zhou, Ivan Rusyn, Fred A Wright

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

48 citing papers in PubMed, 71 citations in OpenAlex.

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  5. A workflow for human health hazard evaluation using transcriptomic data and Key Characteristics-based gene sets.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
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  9. Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025
    Review
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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

6 authors at 2 institutions in 1 country.

John S HouseBioinformatics Research Center, North Carolina State University, Raleigh, NC, United States.
Fabian A GrimmDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States.
Dereje D JimaBioinformatics Research Center, North Carolina State University, Raleigh, NC, United States.
Yi-Hui ZhouBioinformatics Research Center, North Carolina State University, Raleigh, NC, United States.
Ivan RusynDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States.
Fred A WrightBioinformatics Research Center, North Carolina State University, Raleigh, NC, United States.
North Carolina State University · USTexas A&M University · US

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Weihsueh A Chiu · 2017 to 2026
$21.2M
NIEHS NIH HHS P42 ES027704
6 · The paper itself

Abstract

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for

Indexed as

bioinformatics & computational biologybioinformatics-pipelinecardiomyocytesdose–response modelingexpression-based dose–response modelingexpression profilingiPSCstoxicogenomics

Identifiers

PMID29163636
PMCPMC5672545
OpenAlexW2766283631

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.