AIMC Topic: Gene Regulatory Networks

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Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision.

Biology direct
INTRODUCTION: Diabetic nephropathy (DN) is a common diabetes-related complication with unclear underlying pathological mechanisms. Although recent studies have linked glycolysis to various pathological states, its role in DN remains largely underexpl...

Establishment of a nomogram model based on immune-related genes using machine learning for aortic dissection diagnosis and immunomodulation assessment.

International journal of medical sciences
The clinical manifestation of aortic dissection (AD) is complex and varied, making early diagnosis crucial for patient survival. This study aimed to identify immune-related markers to establish a nomogram model for AD diagnosis. Three datasets from G...

Biocomputing at the crossroad between emulating artificial intelligence and cellular supremacy.

Current opinion in biotechnology
Biocomputation aims to create sophisticated biological systems capable of addressing important problems in (bio)medicine with a machine-like precision. At present, computational gene networks engineered by single- or multi-layered assembly of DNA-, R...

Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

The journal of headache and pain
BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associ...

AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.

eLife
Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. The emerging field of diverse intelligence investigates the problem-solvi...

Identification of hub genes and immune-related pathways in acute myeloid leukemia: insights from bioinformatics and experimental validation.

Frontiers in immunology
BACKGROUND: This study aims to identify the hub genes and immune-related pathways in acute myeloid leukemia (AML) to provide new theories for immunotherapy.

Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning.

Nature biomedical engineering
Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the dev...

A machine learning model and identification of immune infiltration for chronic obstructive pulmonary disease based on disulfidptosis-related genes.

BMC medical genomics
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic and progressive lung disease. Disulfidptosis-related genes (DRGs) may be involved in the pathogenesis of COPD. From the perspective of predictive, preventive, and personalized medi...