Evidence map›Paper›PMID 32326418›Full record

ReviewNanomaterials (Basel, Switzerland)2020

Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects.

Pia Anneli Sofia Kinaret, Angela Serra, Antonio Federico, Pekka Kohonen, Penny Nymark, Irene Liampa, My Kieu Ha, Jang-Sik Choi, Karolina Jagiello, Natasha Sanabria and 10 more

Open access · goldAbstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Analytical choices drive toxicogenomic potency estimates: a systematic evaluation of transcriptomic points of departure.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  12. Article
  13. Machine learning to dissect perturbations in complex cellular systems.Computational and structural biotechnology journal · 2025
    Review
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Imaging biofilms using fluorescenceFrontiers in cellular and infection microbiology · 2023
    Review
  20. 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

20 authors at 9 institutions in 7 countries.

Pia Anneli Sofia KinaretFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0002-3312-5331
Angela SerraFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0002-3374-1492
Antonio FedericoFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0003-2554-9879
Pekka KohonenInstitute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden.ORCID 0000-0002-7845-3611
Penny NymarkInstitute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden.ORCID 0000-0002-3435-7775
Irene LiampaSchool of Chemical Engineering, National Technical University of Athens, 15780 Athens, Greece.ORCID 0000-0002-6350-6776
My Kieu HaCenter for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea.
Jang-Sik ChoiCenter for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea.
Karolina JagielloQSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland.ORCID 0000-0002-2730-6873
Natasha SanabriaNational Institute for Occupational Health, Johannesburg 2000, South Africa.ORCID 0000-0002-1613-6178
Georgia MelagrakiNanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus.ORCID 0000-0001-7547-2342
Luca CattelaniFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0003-4852-2310
Michele FratelloFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0002-3997-2339
Haralambos SarimveisSchool of Chemical Engineering, National Technical University of Athens, 15780 Athens, Greece.
Antreas AfantitisNanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus.ORCID 0000-0002-0977-8180
Tae-Hyun YoonCenter for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-2743-6360
Mary GulumianNational Institute for Occupational Health, Johannesburg 2000, South Africa.
Roland GrafströmInstitute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden.
Tomasz PuzynQSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland.ORCID 0000-0003-0449-8339
Dario GrecoFaculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland.ORCID 0000-0001-9195-9003
Tampere University · FIHanyang Cyber University · KRKarolinska Institutet · SENational Technical University of Athens · GRNovaMechanics (Cyprus) · CYUniversity of Gdańsk · PLUniversity of Helsinki · FINational Institute for Occupational Health · ZAUniversity of the Witwatersrand · ZA

Funding

Academy of Finland 322761H2020 NanoinformaTIX 814426H2020 NanoSolveIT 814572
6 · The paper itself

Abstract

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

Indexed as

alternative risk assessmentengineered nanomaterials (ENM)experimental designhigh throughputmicroarrayssequencingtoxicogenomics (TGx)toxicologytranscriptomics

Identifiers

PMID32326418
PMCPMC7221878
OpenAlexW3016893324

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.