Evidence map›Paper›PMID 35731990›Full record

ArticleBriefings in bioinformatics2022

Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.

Raquel Pagano-Márquez, José Córdoba-Caballero, Beatriz Martínez-Poveda, Ana R Quesada, Elena Rojano, Pedro Seoane, Juan A G Ranea, Miguel Ángel Medina

Open access · greenAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 1 country.

Raquel Pagano-MárquezDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
José Córdoba-CaballeroDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Beatriz Martínez-PovedaDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Ana R QuesadaDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Elena RojanoDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Pedro SeoaneDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Juan A G RaneaDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Miguel Ángel MedinaDepartment of Molecular Biology and Biochemistry, University of Malaga, Andalucia Tech, Bulevar Louis Pasteur 31, E-29071, Malaga, Spain.
Universidad de Málaga · ESInstituto de Investigación de Enfermedades Raras · ESInstituto de Investigación Biomédica de Málaga · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAngiogenesis is regulated by multiple genes whose variants can lead to different disorders. Among them, rare diseases are a heterogeneous group of pathologies, most of them genetic, whose information may be of interest to determine the still unknown genetic and molecular causes of other diseases. In this work, we use the information on rare diseases dependent on angiogenesis to investigate the genes that are associated with this biological process and to determine if there are interactions between the genes involved in its deregulation.

resultsWe propose a systemic approach supported by the use of pathological phenotypes to group diseases by semantic similarity. We grouped 158 angiogenesis-related rare diseases in 18 clusters based on their phenotypes. Of them, 16 clusters had traceable gene connections in a high-quality interaction network. These disease clusters are associated with 130 different genes. We searched for genes associated with angiogenesis througth ClinVar pathogenic variants. Of the seven retrieved genes, our system confirms six of them. Furthermore, it allowed us to identify common affected functions among these disease clusters. AVAILABILITY: https://github.com/ElenaRojano/angio_cluster. CONTACT: seoanezonjic@uma.es and elenarojano@uma.es.

Indexed as

Computational BiologyRare DiseasesAlgorithmsCluster AnalysisHumansPhenotypeSemanticsangiogenesisdisease clusteringrare diseasessemantic similaritysystems biology

Identifiers

PMID35731990
PMCPMC9294413
OpenAlexW4283257049

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.