Evidence map›Paper›PMID 27731320›Full record

ArticleScientific reports2016

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules.

Matteo Bersanelli, Ettore Mosca, Daniel Remondini, Gastone Castellani, Luciano Milanesi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

26 citing papers in PubMed, 43 citations in OpenAlex.

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  14. Differential Network Analysis Reveals Regulatory Patterns in Neural Stem Cell Fate Decision.Interdisciplinary sciences, computational life sciences · 2021
    Article
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  16. Systems biology analysis identifiesComputational and structural biotechnology journal · 2021
    Article
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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 at 3 institutions in 2 countries.

Matteo BersanelliDepartment of Physics and Astronomy, Universita'di Bologna, Bologna, Via B. Pichat 6/2, 40127, Italy.
Ettore MoscaInstitute of Biomedical Technologies, National Research Council, Segrate (MI), via Fratelli Cervi 93, 20090, Italy.
Daniel RemondiniDepartment of Physics and Astronomy, Universita'di Bologna, Bologna, Via B. Pichat 6/2, 40127, Italy.
Gastone CastellaniDepartment of Physics and Astronomy, Universita'di Bologna, Bologna, Via B. Pichat 6/2, 40127, Italy.
Luciano MilanesiInstitute of Biomedical Technologies, National Research Council, Segrate (MI), via Fratelli Cervi 93, 20090, Italy.
University of Bologna · ITNational Academies of Sciences, Engineering, and Medicine · USNational Research Council · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD.

Identifiers

PMID27731320
PMCPMC5059623
OpenAlexW2531532678

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.