Bioinformatics analysis of the diversity of gut microbiota and different microbiota on insulin resistance in diabetes mellitus patients

Guo, Qian

doi:10.1016/j.heliyon.2023.e22117

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…Weighted gene coexpression network analysis (WGCNA) has been widely used to identify central genes in clinically important modules by constructing gene coexpression networks [11]. Microarray data and high-throughput sequencing technology are widely used in gene sequencing for screening differentially expressed genes and have shown enormous potential in medical research because of their high diagnostic performance for various diseases [12] [13]. However, to date, a multibiomarker-based diagnostic model has not been developed for the diagnosis of hypertension.…”

Section: Introductionmentioning

confidence: 99%

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Chang,

Guo,

Zou

et al. 2024

WJCD

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Background: Hypertension, also known as increased blood pressure, is a phenomenon in which blood flows in blood vessels and causes persistently higher-than-normal pressure on the vessel wall. The identification of novel prognostic and pathogenesis biomarkers plays a key role in the management of hypertension. Methods: The GSE7483 and GSE75815 datasets from the gene expression omnibus (GEO) database were used to identify the genes associated with hypertension that were differentially expressed genes (DEGs). The functional role of the DEGs was elucidated by gene body (GO) enrichment analysis. In addition, we performed an immune infiltration assay and GSEA on the DEGs of hypertensive patients and verified the expression of novel DEGs in the blood of hypertensive patients by RT-qPCR. Results: A total of 267 DEGs were identified from the GEO database. GO analysis revealed that these genes were associated mainly with biological processes such as fibroblast proliferation, cell structural organization, extracellular matrix organization, vasculature development regulation, and angiogenesis. We identified five possible biomarkers, Ecm1, Sparc, Sphk1, Thbsl, and Mecp2, which correlate with vascular development and angiogenesis characteristic of

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Section: Introductionmentioning

confidence: 99%

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Chang,

Guo,

Zou

et al. 2024

WJCD

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Unveiling the World of Bioinformatics

Dhiman,

Dhiman

2024

Applying Machine Learning Techniques to Bioinformatics

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This chapter take a fascinating voyage across the complex bioinformatics landscapes. The authors begin by defining bioinformatics as the essential connection that connects unprocessed biological data to useful knowledge, laying the groundwork for an investigation into the core fields of proteomics, genomics, and data mining. The story flows naturally, showing how feature refinement techniques, machine learning's predictive power, and deep learning's revolutionary ability to understand intricate biological processes all work together in harmony. Applications in the real world emerge, demonstrating the palpable effects of bioinformatics on drug discovery, the prediction of protein functionality, and the rapidly expanding field of personalised medicine. But this journey is not without its difficulties; we must negotiate the nuances of data integration, contend with the interpretability of machine learning models, fight with moral dilemmas, and face the computing demands of big data. Every obstacle turns into a doorway for creativity.

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Bioinformatics analysis of the diversity of gut microbiota and different microbiota on insulin resistance in diabetes mellitus patients

Cited by 2 publications

References 25 publications

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Unveiling the World of Bioinformatics

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