Evidence map›Paper›PMID 41972011›Full record

ArticleNAR genomics and bioinformatics2026

T-ChroNet: Time-aware chromatin network reconstruction to detect dynamic regulatory programs in longitudinal epigenetic dataset.

Stefano Di Giovenale, Ottavio Lischio, Clelia Cortile, Giacomo Corleone, Maurizio Fanciulli, Francesco Bonchi, Iros Barozzi

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 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

7 authors.

Stefano Di GiovenaleGene Expression and Cancer Models Unit, Department of Research and Advanced Technologies Translational Research Area, IRCCS Regina Elena National Cancer Institute, Rome 00144, Italy.ORCID https://orcid.org/0000-0002-2484-7308
Ottavio LischioGene Expression and Cancer Models Unit, Department of Research and Advanced Technologies Translational Research Area, IRCCS Regina Elena National Cancer Institute, Rome 00144, Italy.
Clelia CortileGene Expression and Cancer Models Unit, Department of Research and Advanced Technologies Translational Research Area, IRCCS Regina Elena National Cancer Institute, Rome 00144, Italy.
Giacomo CorleoneGene Expression and Cancer Models Unit, Department of Research and Advanced Technologies Translational Research Area, IRCCS Regina Elena National Cancer Institute, Rome 00144, Italy.
Maurizio FanciulliGene Expression and Cancer Models Unit, Department of Research and Advanced Technologies Translational Research Area, IRCCS Regina Elena National Cancer Institute, Rome 00144, Italy.
Francesco BonchiIntesa Sanpaolo AI Research, Turin 10138, Italy.
Iros BarozziCenter for Cancer Research, Medical University of Vienna, Borschkegasse 8a, Vienna 1090, Austria.ORCID https://orcid.org/0000-0003-0690-3473

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Networks are widely applied to investigate relationships among individual components of complex biological systems. Recent application of biological networks, such as gene co-expression networks and gene regulatory networks, has been instrumental to define principles of transcriptional modulation in development and disease. However, computational methods that can embed the activity of

Indexed as

ChromatinComputational BiologyEpigenesis, GeneticGene Regulatory NetworksAnimalsHistonesHumansMiceChromatinHistones

Identifiers

PMID41972011
PMCPMC13069678

What OpenQuestion holds

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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.