AIMC Topic: Protein Interaction Maps

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Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Scientific reports
Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, environmental factors, and lifestyle choices. With the rising prevalence and increasing associated chronic complications, identifying and understanding ...

Machine learning unveils hypoxia-immune gene hub for clinical stratification of thyroid-associated ophthalmopathy.

Scientific reports
Thyroid-associated ophthalmopathy (TAO) is an autoimmune disorder affecting the orbit, potentially resulting in blindness. This study focused on the role of hypoxia in its pathogenesis through integrative bioinformatics and experimental validation. F...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Scientific reports
Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized by high metastatic potential and recurrence rates. Investigations into the molecular mechanisms and therapeutic targets of ccRCC have provided novel d...

Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning.

Scientific reports
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...

Human protein interaction networks of ancestral and variant SARS-CoV-2 in organ-specific cells and bodily fluids.

Nature communications
Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infection is essential for developing effective COVID-19 antivirals. However, how the ancestral virus and its variants remodel virus-host protein assemblies i...

Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics.

Scientific reports
Cholesterol metabolism-related genes (CMRGs) have been associated with osteoarthritis (OA), but their specific regulatory mechanisms remain unclear. This study aimed to investigate the role of CMRGs in OA and provide new insights into its treatment. ...

Identification of pyroptosis related genes and subtypes in atherosclerosis using multiomic and single cell analysis.

Scientific reports
Atherosclerosis (AS), the leading cause of cardiovascular diseases, is a chronic inflammatory disorder involving lipid metabolism, immune dysregulation, and cell death. Pyroptosis, a form of inflammatory programmed cell death, is implicated in AS pro...

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...

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...

Exploration of the potential therapeutic effects and targets of Coriandrum sativum on non-erosive esophagitis based on bioinformatics and molecular dynamics simulation.

Scientific reports
Gastroesophageal reflux disease (GERD) is one of the most frequently diagnosed gastrointestinal disorders, adversely affecting quality of life. Coriandrum sativum has been shown to effectively promote gastrointestinal motility, alleviate gastric disc...