Evidence map›Paper›PMID 38660909›Full record

ReviewZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2024

[Research progress on bioinformatics in pulmonary arterial hypertension].

Wei Peng, Ze-Ying Zhang, Yun-Bin Xiao

Open access · greenAbstract readReviewEnglish Abstract
In one paragraph

Review in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 2024. 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, top 89% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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 at 1 institution in 1 country.

Wei PengSchool of Pediatrics, University of South China, Changsha 410007, China.
Ze-Ying Zhang
Yun-Bin XiaoSchool of Pediatrics, University of South China, Changsha 410007, China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a severe disease characterized by abnormal pulmonary vascular remodeling and increased right ventricular pressure load, posing a significant threat to patient health. While some pathological mechanisms of PAH have been revealed, the deeper mechanisms of pathogenesis remain to be elucidated. In recent years, bioinformatics has provided a powerful tool for a deeper understanding of the complex mechanisms of PAH through the integration of techniques such as multi-omics analysis, artificial intelligence, and Mendelian randomization. This review focuses on the bioinformatics methods and technologies used in PAH research, summarizing their current applications in the study of disease mechanisms, diagnosis, and prognosis assessment. Additionally, it analyzes the existing challenges faced by bioinformatics and its potential applications in the clinical and basic research fields of PAH in the future.

Indexed as

Computational BiologyPulmonary Arterial HypertensionHumansHypertension, PulmonaryArtificial intelligenceBioinformaticsMachine learningPulmonary arterial hypertension

Identifiers

PMID38660909
PMCPMC11057300
OpenAlexW4395465876

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.