AIMC Topic: Gene Regulatory Networks

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Triclosan exposure potentiates ischemic stroke risk: Multi-omics integration and molecular docking unveil neurotoxic mechanisms.

Ecotoxicology and environmental safety
This study applied network toxicology and multimodal biological approaches integrated with machine learning to systematically identify four TCS-IS-related genes, providing a comprehensive understanding of the pathophysiological relationship between t...

Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks.

Journal of chemical information and modeling
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
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
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...

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Scientific reports
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
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...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Scientific reports
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
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...

Immuno-transcriptomic analysis based on machine learning identifies immunity signature genes of chronic rhinosinusitis with nasal polyps.

Scientific reports
Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent inflammatory disease where immunomodulation plays a pivotal role. However, immuno-transcriptomic characteristics and its clinical relevance remains largely known. We analyzed transcript...

Integrative machine learning identifies robust inflammation-related diagnostic biomarkers and stratifies immune-heterogeneous subtypes in Kawasaki disease.

Pediatric rheumatology online journal
BACKGROUND: Kawasaki disease (KD), a pediatric systemic vasculitis, lacks reliable diagnostic biomarkers and exhibits immune heterogeneity, complicating clinical management. Current therapies face challenges in targeting specific immune pathways and ...