Evidence map›Paper›PMID 41423050›Full record

ArticleMolecular & cellular proteomics : MCP2026

Post-Transcriptional Modification Integration for Ligand-Receptor Cellular Network Inference.

Pierre Giroux, Morgan Maillard, Jacques Colinge

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Pierre GirouxIRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Montpellier, France; Université de Montpellier, Montpellier, France; ICM, Institut régional du Cancer de Montpellier, Montpellier, France.
Morgan MaillardIRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Montpellier, France; Université de Montpellier, Montpellier, France; ICM, Institut régional du Cancer de Montpellier, Montpellier, France.
Jacques ColingeIRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Montpellier, France; Université de Montpellier, Montpellier, France; ICM, Institut régional du Cancer de Montpellier, Montpellier, France. Electronic address: jacques.colinge@umontpellier.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-cell communications are widely explored to understand tissue homeostasis and diseases. Numerous computational tools have been developed to infer cellular interactions from transcriptomic or proteomic expression data. However, proteins often carry post-translational modifications (PTMs) that can induce conformational switches and alter their functional properties. A key challenge remains to incorporate PTM data in the inference and analysis of cellular interactions. Here, we propose an extension of our previously published tool BulkSignalR to integrate PTM information in ligand-receptor interactions and downstream pathway predictions. This new functionality is compatible with bulk and single-cell data, and it supports all types of PTMs. Based on two illustrative datasets, we show that this new feature provides deeper insights into biological pathway regulation and that PTM integration helps reduce false-positive results occasionally produced by standard approaches.

Indexed as

Computational BiologyProtein Processing, Post-TranslationalHumansLigandsProteomicsLigandsligand–receptor interactionspost-translational modificationsproteomics data integration

Identifiers

PMID41423050
PMCPMC12933558

What OpenQuestion holds

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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 OpenQuestion graph.