ArticleBMC systems biology2012
Preeclampsia: a bioinformatics approach through protein-protein interaction networks analysis.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- Pooled it
- Integrative transcriptome analysis reveals dysregulation of canonical cancer molecular pathways in placenta leading to preeclampsia.Scientific reports · 2013Pooled it
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- Type I interferon exposure of an implantation-on-a-chip device alters invasive extravillous trophoblast function.Cell reports. Medicine · 2025Article
- Liquid-Liquid Phase Separation Associated with Intrinsically Disordered Proteins: Experimental and Computational Tools.Current protein & peptide science · 2025Review
- Bioinformatics Strategies to Identify Shared Molecular Biomarkers That Link Ischemic Stroke and Moyamoya Disease with Glioblastoma.Pharmaceutics · 2022Article
- Identifying preeclampsia-associated genes using a control theory method.Briefings in functional genomics · 2022Article
- Network based systems biology approach to identify diseasome and comorbidity associations of Systemic Sclerosis with cancers.Heliyon · 2022Article
- Network medicine in Cardiovascular Research.Cardiovascular research · 2021Review
- A Multi-Objective Approach for Drug Repurposing in Preeclampsia.Molecules (Basel, Switzerland) · 2021Article
- Comprehensive Analysis of Differently Expressed and Methylated Genes in Preeclampsia.Computational and mathematical methods in medicine · 2020Article
- Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis.Oncology letters · 2019Article
- Candidate Gene, Genome-Wide Association and Bioinformatic Studies in Pre-eclampsia: a Review.Current hypertension reports · 2018Review
- Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis.BMC medical genomics · 2017Article
- Placental transcriptome co-expression analysis reveals conserved regulatory programs across gestation.BMC genomics · 2017Article
- Evidence of perturbations of the cytokine network in preterm labor.American journal of obstetrics and gynecology · 2015Article
- PolySearch2: a significantly improved text-mining system for discovering associations between human diseases, genes, drugs, metabolites, toxins and more.Nucleic acids research · 2015Article
- Co-expression network analysis and genetic algorithms for gene prioritization in preeclampsia.BMC medical genomics · 2013Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn this study we explored preeclampsia through a bioinformatics approach. We create a comprehensive genes/proteins dataset by the analysis of both public proteomic data and text mining of public scientific literature. From this dataset the associated protein-protein interaction network has been obtained. Several indexes of centrality have been explored for hubs detection as well as the enrichment statistical analysis of metabolic pathway and disease.
resultsWe confirmed the well known relationship between preeclampsia and cardiovascular diseases but also identified statistically significant relationships with respect to cancer and aging. Moreover, significant metabolic pathways such as apoptosis, cancer and cytokine-cytokine receptor interaction have also been identified by enrichment analysis. We obtained FLT1, VEGFA, FN1, F2 and PGF genes with the highest scores by hubs analysis; however, we also found other genes as PDIA3, LYN, SH2B2 and NDRG1 with high scores.
conclusionsThe applied methodology not only led to the identification of well known genes related to preeclampsia but also to propose new candidates poorly explored or completely unknown in the pathogenesis of preeclampsia, which eventually need to be validated experimentally. Moreover, new possible connections were detected between preeclampsia and other diseases that could open new areas of research. More must be done in this area to resolve the identification of unknown interactions of proteins/genes and also for a better integration of metabolic pathways and diseases.
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Registered trials
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.