AIMC Topic: Gene Regulatory Networks
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Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.
Journal of translational medicine
Mar 4, 2025
BACKGROUND: Single-cell multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of cellular heterogeneity and development by providing insights into gene expression at the single-cell level...
Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and exploration of its potential mechanism of action using animal experiments.
Frontiers in immunology
Mar 4, 2025
BACKGROUND: Acute kidney injury (AKI) after kidney transplantation is one of the main causes of graft loss and poor patient prognosis, and it is important to explore new targets for treating AKI in kidney transplantation.
The role of senescence-related genes in major depressive disorder: insights from machine learning and single cell analysis.
BMC psychiatry
Mar 3, 2025
BACKGROUND: Evidence indicates that patients with Major Depressive Disorder (MDD) exhibit a senescence phenotype or an increased susceptibility to premature senescence. However, the relationship between senescence-related genes (SRGs) and MDD remains...
Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.
Artificial cells, nanomedicine, and biotechnology
Mar 1, 2025
Ageing significantly contributes to osteoarthritis (OA) and metabolic syndrome (MetS) pathogenesis, yet the underlying mechanisms remain unknown. This study aimed to identify ageing-related biomarkers in OA patients with MetS. OA and MetS datasets an...
GALR1 and PENK serve as potential biomarkers in invasive non-functional pituitary neuroendocrine tumours.
Gene
Feb 28, 2025
BACKGROUND: Some nonfunctioning pituitary neuroendocrine tumor (NFPitNET) can show invasive growth, which increases the difficulty of surgery and indicates a poor prognosis. However, the molecular mechanism related to invasiveness remains to be furth...
Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study.
Frontiers in immunology
Feb 27, 2025
INTRODUCTION: Knee osteoarthritis (KOA) is a degenerative joint disease characterized by the progressive deterioration of cartilage and synovial inflammation. A critical mechanism in the pathogenesis of KOA is impaired efferocytosis in synovial tissu...
Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.
PloS one
Feb 27, 2025
Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide. Early detection of lung cancer can help reduce the death rate; therefore, the identification of potential biomarkers is crucial. Thus, this study ai...
Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis.
Frontiers in immunology
Feb 25, 2025
BACKGROUND: Atherosclerosis is a significant contributor to cardiovascular disease, and conventional diagnostic methods frequently fall short in the timely and accurate detection of early-stage atherosclerosis. Abnormal lipid metabolism plays a criti...
Identification of Biomarkers for Response to Interferon in Chronic Hepatitis B Based on Bioinformatics Analysis and Machine Learning.
Viral immunology
Feb 24, 2025
Interferon (IFN) is a pivotal agent against hepatitis B virus (HBV) in clinic, but there is a lack of accurate biomarkers to predict the response to IFN therapy in patients with chronic hepatitis B (CHB). Our study aimed to investigate potential targ...
Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.
Frontiers in immunology
Feb 24, 2025
BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.
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