Evidence map›Paper›PMID 40190255›Full record

ArticleJournal of cell science2025

Practical considerations for data exploration in quantitative cell biology.

Joanna W Pylvänäinen, Hanna Grobe, Guillaume Jacquemet

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cell science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

3 authors.

Joanna W PylvänäinenTurku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland.ORCID 0000-0002-3540-5150
Hanna GrobeTurku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland.ORCID 0009-0007-3335-1666
Guillaume JacquemetTurku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland.ORCID 0000-0002-9286-920X

Funding

Åbo Akademi UniversityAcademy of Finland 337530Cancer Society of FinlandResearch Council of Finland 338537Sigrid Juselius Foundation
6 · The paper itself

Abstract

Data exploration is an essential step in quantitative cell biology, bridging raw data and scientific insights. Unlike polished, published figures, effective data exploration requires a flexible, hands-on approach that reveals trends, identifies outliers and refines hypotheses. This Opinion offers simple, practical advice for building a structured data exploration workflow, drawing on the authors' personal experience in analyzing bioimage datasets. In addition, the increasing availability of generative artificial intelligence and large language models makes coding and improving data workflows easier than ever before. By embracing these practices, researchers can streamline their workflows, produce more reliable conclusions and foster a collaborative, transparent approach to data analysis in cell biology.

Indexed as

Cell BiologyComputational BiologyData AnalysisArtificial IntelligenceHumansData analysisData explorationData managementMicroscopy

Identifiers

PMID40190255
PMCPMC12045597

What Socratic 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 Socratic graph.