AIMC Topic: Gene Regulatory Networks

Clear Filters Showing 171 to 180 of 830 articles

Frustration in physiology and molecular medicine.

Molecular aspects of medicine
Molecules provide the ultimate language in terms of which physiology and pathology must be understood. Myriads of proteins participate in elaborate networks of interactions and perform chemical activities coordinating the life of cells. To perform th...

Identification of Mitochondrial and Succinylation Modification-Related Gene Signature in Ischemic Stroke.

Molecular neurobiology
Ischemic stroke (IS) is a leading cause of death and disability worldwide, often associated with immune dysregulation, mitochondrial dysfunction, and altered protein succinylation. This study aimed to identify mitochondrial and succinylation-related ...

Integrating WGCNA and SVM-RFE identifies hub molecular biomarkers driving ischemic stroke progression.

Neurological research
BACKGROUND: Stroke is the second most common cause of death worldwide and the leading cause of long-term severe disability with neurological impairment worsening within hours after stroke onset and being especially involved with motor function. So fa...

Bioinformatics Approach to Identifying Molecular Targets of Isoliquiritigenin Affecting Chronic Obstructive Pulmonary Disease: A Machine Learning Pharmacology Study.

International journal of molecular sciences
To identify the molecular targets and possible mechanisms of isoliquiritigenin (ISO) in affecting chronic obstructive pulmonary disease (COPD) by regulating the glycolysis and phagocytosis of alveolar macrophages (AM). Datasets GSE130928 and GSE13896...

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

BMC bioinformatics
BACKGROUND: A gene regulatory network (GRN) is a graph-level representation that describes the regulatory relationships between transcription factors and target genes in cells. The reconstruction of GRNs can help investigate cellular dynamics, drug d...

Identification of key therapeutic targets in nicotine-induced intracranial aneurysm through integrated bioinformatics and machine learning approaches.

BMC pharmacology & toxicology
BACKGROUND: Intracranial aneurysm (IA) is a critical cerebrovascular condition, and nicotine exposure is a known risk factor. This study delves into the toxicological mechanisms of nicotine in IA, aiming to identify key biomarkers and therapeutic tar...

Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in intracranial aneurysma.

Frontiers in immunology
BACKGROUND: Increasing evidence indicates a connection between intracranial aneurysm (intracranial aneurysm, IA) and autoimmune diseases. However, the molecular mechanisms from a genetic perspective remain unclear. This study aims to elucidate the po...

The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.

Frontiers in immunology
OBJECTIVE: Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. This study aims to investigate the relationship between gene e...

Identification and Validation of Ferritinophagy-Related Biomarkers in Periodontitis.

International dental journal
OBJECTIVE: While ferritinophagy is believed to play a significant role in the development of periodontitis, the exact mechanisms remain unclear. This study aimed to investigate the biomarkers associated with ferritinophagy in periodontitis using tran...

Revealing the Oxidative Stress-Related Molecular Characteristics and Potential Therapeutic Targets of Schizophrenia through Integrated Gene Expression Data Analysis.

Molecular neurobiology
Schizophrenia is a severe mental disorder characterized by oxidative stress imbalances. The underlying mechanisms of oxidative stress-related gene expression in schizophrenia require further investigation. Additionally, the diagnosis of schizophrenia...