AIMC Topic: Gene Regulatory Networks
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Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning.
Scientific reports
Jul 1, 2025
Early detection of lung nodules (LNs) is critical for prevention and treatment of lung cancer. However, current noninvasive diagnostic methods face significant challenges in reliably distinguishing benign from malignant nodules. Thus, there is an urg...
Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data.
Nature communications
Jul 1, 2025
During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq d...
Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks.
Journal of chemical information and modeling
Jun 12, 2025
Competitive endogenous RNA (ceRNA) regulatory networks (CENA) have advanced our understanding of noncoding RNAs' roles in complex diseases, providing a theoretical basis for disease mechanisms. Existing ceRNA-disease association prediction methods ar...
Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.
Clinical and experimental medicine
Jun 12, 2025
Lactylation, a novel post-translational modification, has been implicated in various pathophysiological processes; however, its role in sepsis-associated acute kidney injury (SA-AKI) remains unclear. This study aimed to investigate the expression pat...
Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.
Functional & integrative genomics
Jun 9, 2025
Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (MetS). However, the underlying genetic and molecular mechanisms remain insufficiently elucidated. Th...
Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.
Artificial cells, nanomedicine, and biotechnology
Jun 6, 2025
Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multiple immune and inflammatory factors. Macrophages play a crucial role in its development. This study integrated scRNA-seq and RNA-seq data to explore m...
Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.
Scientific reports
Jun 5, 2025
Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, and the mesenchymal type is the most aggressive form with the worst prognosis. GBM undergoes proneura...
Epistasis regulates genetic control of cardiac hypertrophy.
Nature cardiovascular research
Jun 5, 2025
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...
Epistasis, Genetic
Induced Pluripotent Stem Cells
Connectin
Ventricular Remodeling
Myocytes, Cardiac
Hypertrophy, Left Ventricular
Deep Learning
Genome-Wide Association Study
Gene Regulatory Networks
Receptor, IGF Type 1
Heart Failure
Genetic Predisposition to Disease
Magnetic Resonance Imaging
Aged
Male
Middle Aged
Humans
Phenotype
Female
Identification of key proteins and pathways in myocardial infarction using machine learning approaches.
Scientific reports
Jun 4, 2025
Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning...
Efficient structure learning of gene regulatory networks with Bayesian active learning.
BMC bioinformatics
Jun 3, 2025
BACKGROUND: Gene regulatory network modeling is a complex structure learning problem that involves both observational data analysis and experimental interventions. Bayesian causal discovery provides a principled framework for modeling observational d...
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