Evidence map›Paper›PMID 34684861›Full record

ArticleMolecules (Basel, Switzerland)2021

Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition-Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils.

Alessio Ragno, Anna Baldisserotto, Lorenzo Antonini, Manuela Sabatino, Filippo Sapienza, Erika Baldini, Raissa Buzzi, Silvia Vertuani, Stefano Manfredini

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecules (Basel, Switzerland), 2021. 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
0.6field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  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

9 authors at 2 institutions in 1 country.

Alessio RagnoDepartment of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University, 00185 Rome, Italy.ORCID 0000-0002-8477-2088
Anna BaldisserottoDepartment of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy.ORCID 0000-0002-2882-3530
Lorenzo AntoniniDepartment of Drug Chemistry and Technology, Sapienza University, 00185 Rome, Italy.
Manuela SabatinoDepartment of Drug Chemistry and Technology, Sapienza University, 00185 Rome, Italy.ORCID 0000-0001-9127-3925
Filippo SapienzaDepartment of Drug Chemistry and Technology, Sapienza University, 00185 Rome, Italy.
Erika BaldiniDepartment of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy.
Raissa BuzziDepartment of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy.
Silvia VertuaniDepartment of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy.
Stefano ManfrediniDepartment of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy.ORCID 0000-0003-1348-4422
University of Ferrara · ITSapienza University of Rome · IT

Funding

Ambrosialab Grant 2020Università degli Studi di Ferrara FAR 2020
6 · The paper itself

Abstract

Scientific investigation on essential oils composition and the related biological profile are continuously growing. Nevertheless, only a few studies have been performed on the relationships between chemical composition and biological data. Herein, the investigation of 61 assayed essential oils is reported focusing on their inhibition activity against

Indexed as

Machine LearningAnti-Infective AgentsArthrodermataceaeComplex MixturesData CollectionMicrosporumOils, VolatilePhylogenyStructure-Activity RelationshipAnti-Infective AgentsComplex MixturesOils, Volatilecosmeceuticsdeep learningessential oilsmachine learningnutraceuticspharmaceuticsQCAR

Identifiers

PMID34684861
PMCPMC8537614
OpenAlexW3205709618

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.