Evidence map›Paper›PMID 42056689›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

PhyloSystemX: Enhancing the Analysis of Interaction Networks.

Hugo Bonnefous, Yu Zhang, Philippe Lopez, François-Joseph Lapointe, Eric Bapteste

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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

5 authors.

Hugo BonnefousDepartment of Computational, Quantitative and Synthetic Biology (CQSB), UMR7238, Sorbonne Université, CNRS, IBPS, 75005, Paris, France.
Yu ZhangDepartment of Computational, Quantitative and Synthetic Biology (CQSB), UMR7238, Sorbonne Université, CNRS, IBPS, 75005, Paris, France.
Philippe LopezDepartment of Computational, Quantitative and Synthetic Biology (CQSB), UMR7238, Sorbonne Université, CNRS, IBPS, 75005, Paris, France.
François-Joseph LapointeDépartement de Sciences Biologiques, Complexe Des Sciences, Université de Montréal, Montréal, QC, Canada.
Eric BaptesteDepartment of Computational, Quantitative and Synthetic Biology (CQSB), UMR7238, Sorbonne Université, CNRS, IBPS, 75005, Paris, France. epbapteste@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PhyloSystemX is a computational tool designed to reconstruct ancestral biological interaction networks by integrating phylogenetic species trees with modern interaction data. While systems biologists commonly use networks to represent complex biological interactions, contemporary network analysis alone cannot reveal the evolutionary history that shaped these systems. PhyloSystemX addresses this gap by implementing parsimony-based algorithms (Dollo and Sankoff adjusted algorithm) to infer both ancestral vertices (homology groups) and their interactions across evolutionary time. Unlike tools limited to specific interaction types, PhyloSystemX can analyze any network whose vertices can be labeled with homology identifiers, including protein-protein interactions, gene co-expression networks, and metabolic regulation systems. By inferring ancestral networks, researchers can uncover evolutionarily conserved functional modules, identify lineage-specific innovations, and explore how biological systems adapt over time. The current implementation assumes vertical inheritance of traits, with limitations regarding introgression, hybridization, and horizontal gene transfer that future versions may address.

Indexed as

Computational BiologyGene Regulatory NetworksSoftwareSystems BiologyAlgorithmsAnimalsEvolution, MolecularPhylogenyProtein Interaction MapsAncestral network reconstructionEvolutionary biologyInteraction networksNetwork evolutionPhylogeneticsSystems biology

Identifiers

PMID42056689

What Socratic holds

Textmetadata
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.