AIMC Topic: Kruppel-Like Factor 4

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Multi-tissue Methylation Analysis of Alzheimer's Disease: Insights into Pathways, Modules, and Key Genes.

Journal of molecular neuroscience : MN Jul 16, 2025
DNA methylation plays a crucial role in the onset and progression of Alzheimer's disease (AD). Genome-wide methylation analysis of multi-tissue data can provide insights into the pathology and diagnostic biomarkers of AD. Computational tools were emp...
Humans Female Aged Male Cell Line, Tumor Protein Interaction Maps Gene Regulatory Networks DNA Methylation Transforming Growth Factor beta1 Neurons Alzheimer Disease Kruppel-Like Factor 4 Kruppel-Like Transcription Factors Hypoxia-Inducible Factor 1, alpha Subunit Neuroglia Thrombospondin 1
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Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.

Orphanet journal of rare diseases Jul 10, 2025
OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopathic pulmonary fibrosis (IPF). This study aimed to identify lipid-related genes implicated in IPF pathogenesis.
Humans Machine Learning Prognosis Gene Regulatory Networks Idiopathic Pulmonary Fibrosis Lipid Metabolism Kruppel-Like Factor 4 Kruppel-Like Transcription Factors
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A novel machine learning based approach for iPS progenitor cell identification.

PLoS computational biology Dec 26, 2019
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...
Humans Machine Learning Cells, Cultured Animals Mice Computational Biology Cellular Reprogramming Fibroblasts Models, Biological Kruppel-Like Factor 4 Mouse Embryonic Stem Cells Induced Pluripotent Stem Cells Time-Lapse Imaging
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Identifying Biomarkers of Hepatocellular Carcinoma Based on Gene Co-Expression Network from High-Throughput Data.

Studies in health technology and informatics Jan 1, 2017
In this paper, we proposed an approach systematically based on the use of gene co-expression network analyses to identify potential biomarkers for Hepatocellular Carcinoma (HCC). With the analysis of differential gene expression, we first selected ca...
Humans Biomarkers Gene Expression Profiling Liver Neoplasms Carcinoma, Hepatocellular Gene Regulatory Networks Kruppel-Like Factor 4 Kruppel-Like Transcription Factors
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