Back to search

Article

Multi-omics regulatory networks reveal the key driver genes in the development of type 2 diabetes

2022-08-24

Abstract excerpt

<title>Abstract</title> <p><bold>Background</bold>Type 2 diabetes (T2D) onset is a complex, organized biological process with multilevel regulation, and its physiopathological mechanisms are yet to be elucidated. This study aims to find out the hub genes and pathways involved in the pathogenesis of T2D through multi-omics analysis.<bold>Methods</bold>The datasets used in the experiments com-prise three groups: (1...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
29192f21-d32b-5f53-9318-6772a1f0f4b3
DOI
10.21203/rs.3.rs-1969297/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Multi-omics regulatory networks reveal the key driver genes in the development of type 2 diabetesDOI 10.21203/rs.3.rs-1969297/v1
Uncovering the gene regulatory network of type 2 diabetes through multi-omic data integrationSemantic proximity
Identification and analysis of key genes and signaling pathways associated with Type 1 diabetes mellitus by bioinformatics analysis of next generation sequencing dataSemantic proximity
Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitusSemantic proximity
Analysis of key genes and pathways associated with the pathogenesis of Type 2 diabetes mellitusSemantic proximity
Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes MellitusSemantic proximity
Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysisSemantic proximity
Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysisSemantic proximity
Elucidating the Type 2 Diabetes Regulatory Network: Identification of EGFR as a Key Hub and Novel Drug CandidatesSemantic proximity
Single-Cell RNA Sequencing Analysis of Key Candidate Genes; Molecular Modeling and Docking-Based Therapeutic Molecules Exploration of Nature Derived Phytoconstituents for Type 2 Diabetes Mellitus.Semantic proximity
Bioinformatics and network biology approach to identifying type 2 diabetes genes and pathways that influence the progression of breast cancerSemantic proximity
Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: A bioinformatics analytic workflowSemantic proximity
Discovering hub genes involved in the pathophysiological impact of COVID-19 on diabetes kidney disease by differential gene expression and interactome analysisSemantic proximity
Select a neighboring publication to make it the new centre.