Evidence map›Paper›PMID 39211313›Full record

ArticleBioinformatics advances2024

evolSOM: An R package for analyzing conservation and displacement of biological variables with self-organizing maps.

Santiago Prochetto, Renata Reinheimer, Georgina Stegmayer

Abstract read
In one paragraph

Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Santiago ProchettoInstituto de Agrobiotecnología del Litoral, FBCB-UNL, Universidad Nacional del Litoral, CONICET, CCT-Santa Fe, Santa Fe, 3000, Argentina.ORCID https://orcid.org/0000-0002-8591-149X
Renata ReinheimerInstituto de Agrobiotecnología del Litoral, FBCB-UNL, Universidad Nacional del Litoral, CONICET, CCT-Santa Fe, Santa Fe, 3000, Argentina.
Georgina StegmayerResearch Institute for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, CCT-Santa Fe, Santa Fe, 3000, Argentina.ORCID https://orcid.org/0000-0003-4459-4560

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. Ribonucleic acid molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data present a significant challenge. Results: We introduce evolSOM, a novel R package that allows exploring and visualizing the conservation or displacement of biological variables, easing the integration of phenotypic and genotypic attributes. It enables the projection of multi-dimensional expression profiles onto interpretable two-dimensional grids, aiding in the identification of conserved or displaced genes/phenotypes across multiple conditions. Variables displaced together suggest membership to the same regulatory network, where the nature of the displacement may hold biological significance. The conservation or displacement of variables is automatically calculated and graphically presented by evolSOM. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. Availability and implementation: The package is open-source under the GPL (

Identifiers

PMID39211313
PMCPMC11361812

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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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 Socratic graph.