ReviewBiomedical journal2023
Protein network analysis and functional enrichment via computational biotechnology unravel molecular and pathogenic mechanisms of kidney stone disease.
Review in Biomedical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- Red single wavelength emitting up-conversion nanoparticles modulate cellular dynamics and gene expression in T24 bladder cancer cells.Scientific reports · 2025Article
- Role of UropathogenicPathogens (Basel, Switzerland) · 2025Review
- Validation of the STONE and new STONE score for ureteral stones in elderly patients: a retrospective cohort study.Urolithiasis · 2025Article
- Kidney Stones as Minerals: How Methods from Geology Could Inform Urolithiasis Treatment.Journal of clinical medicine · 2025Review
- Comprehensive biomarker profiling reveals distinct molecular signatures across stone types: a large-scale cross-sectional study in Southern China.Frontiers in physiology · 2025Article
- Introducing dysfunctional Protein-Protein Interactome (dfPPI) - A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease.Current opinion in structural biology · 2024Review
- Pathophysiology and Main Molecular Mechanisms of Urinary Stone Formation and Recurrence.International journal of molecular sciences · 2024Review
- Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare.Briefings in bioinformatics · 2024Review
- An overview of global research landscape in etiology of urolithiasis based on bibliometric analysis.Urolithiasis · 2023Review
- When it doesn't run in the blood(vessels) - events involved in vascular disorders.Biomedical journal · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass spectrometry-based proteomics has been extensively applied to current biomedical research. From such large-scale identification of proteins, several computational tools have been developed for determining protein-protein interactions (PPI) network and functional significance of the identified proteins and their complex. Analyses of PPI network and functional enrichment have been widely applied to various fields of biomedical research. Herein, we summarize commonly used tools for PPI network analysis and functional enrichment in kidney stone research and discuss their applications to kidney stone disease (KSD). Such computational approach has been used mainly to investigate PPI networks and functional significance of the proteins derived from urine of patients with kidney stone (stone formers), stone matrix, Randall's plaque, renal papilla, renal tubular cells, mitochondria and immune cells. The data obtained from computational biotechnology leads to experimental validation and investigations that offer new knowledge on kidney stone formation processes. Moreover, the computational approach may also lead to defining new therapeutic targets and preventive strategies for better outcome in KSD management.
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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.