Evidence map›Paper›PMID 33515236›Full record

ArticleBioinformatics (Oxford, England)2021

Comparison Of Observation-Based And Model-Based Identification Of Alert Concentrations From Concentration-Expression Data.

Franziska Kappenberg, Marianna Grinberg, Xiaoqi Jiang, Annette Kopp-Schneider, Jan G Hengstler, Jörg Rahnenführer

Abstract readComparative Study
In one paragraph

Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Identification of Changes in Gene Expression.Biometrical journal. Biometrische Zeitschrift · 2026
    Article
  2. Article
  3. AlertGS: determining alerts for gene sets.Bioinformatics (Oxford, England) · 2025
    Article
  4. Article
  5. Article
  6. 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

6 authors.

Franziska KappenbergDepartment of Statistics, TU Dortmund University, Dortmund, 44221, Germany.
Marianna GrinbergDepartment of Statistics, TU Dortmund University, Dortmund, 44221, Germany.
Xiaoqi JiangAI Solutions-Services & Core, BASF SE, Ludwigshafen am Rhein, 67061, GermanyPresent address.
Annette Kopp-SchneiderDivision of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany.
Jan G HengstlerLeibniz Research Centre for Working Environment and Human Factors (IfADo), TU Dortmund University, Dortmund, 44139, Germany.
Jörg RahnenführerDepartment of Statistics, TU Dortmund University, Dortmund, 44221, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationAn important goal of concentration-response studies in toxicology is to determine an 'alert' concentration where a critical level of the response variable is exceeded. In a classical observation-based approach, only measured concentrations are considered as potential alert concentrations. Alternatively, a parametric curve is fitted to the data that describes the relationship between concentration and response. For a prespecified effect level, both an absolute estimate of the alert concentration and an estimate of the lowest concentration where the effect level is exceeded significantly are of interest.

resultsIn a simulation study for gene expression data, we compared the observation-based and the model-based approach for both absolute and significant exceedance of the prespecified effect level. Results show that, compared to the observation-based approach, the model-based approach overestimates the true alert concentration less often and more frequently leads to a valid estimate, especially for genes with large variance. AVAILABILITY AND IMPLEMENTATION: The code used for the simulation studies is available via the GitHub repository: https://github.com/FKappenberg/Paper-IdentificationAlertConcentrations. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Computer SimulationAlgorithmsComputational BiologyHumans

Identifiers

PMID33515236
PMCPMC8337003

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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.