AIMC Topic: Gene Ontology

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DeepGOMeta for functional insights into microbial communities using deep learning-based protein function prediction.

Scientific reports
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Tradi...

Novel anoikis-related diagnostic biomarkers for aortic dissection based on machine learning.

Scientific reports
Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is characterized by acute onset and poor prognosis, while the pathogenesis of AD is still unclear and may affect or even delay the diagnosis of AD. Ancho...

Identification and validation of susceptibility modules and hub genes in polyarticular juvenile idiopathic arthritis using WGCNA and machine learning.

Autoimmunity
BACKGROUND: Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflam...

Integration of biological data via NMF for identification of human disease-associated gene modules through multi-label classification.

PloS one
Proteins associated with multiple diseases often interact, forming disease modules that are critical for understanding disease mechanisms. This study integrates protein-protein interactions (PPIs) and Gene Ontology data using non-negative matrix fact...

Gene ontology defines pre-post- hatch energy dynamics in the complexus muscle of broiler chickens.

BMC genomics
BACKGROUND: Chicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provid...

Identification of immune-related mitochondrial metabolic disorder genes in septic shock using bioinformatics and machine learning.

Hereditas
PURPOSE: Mitochondria are involved in septic shock and inflammatory response syndrome, which severely affects the life security of patients. It is necessary to recognize and explore the immune-mitochondrial genes in septic shock.

Identification of biomarkers for the diagnosis in colorectal polyps and metabolic dysfunction-associated steatohepatitis (MASH) by bioinformatics analysis and machine learning.

Scientific reports
Colorectal polyps are precursors of colorectal cancer. Metabolic dysfunction associated steatohepatitis (MASH) is one of metabolic dysfunction associated fatty liver disease (MAFLD) phenotypic manifestations. Much evidence has suggested an associatio...

An experimental analysis of graph representation learning for Gene Ontology based protein function prediction.

PeerJ
Understanding protein function is crucial for deciphering biological systems and facilitating various biomedical applications. Computational methods for predicting Gene Ontology functions of proteins emerged in the 2000s to bridge the gap between the...

Comprehensive Analysis of Immune Infiltration and Key Genes in Peri-Implantitis Using Bioinformatics and Molecular Biology Approaches.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Peri-implantitis is the main cause of failure of implant treatment, and there is little research on its molecular mechanism. This study aimed to identify key biomarkers and immune infiltration of peri-implantitis using a bioinformatics met...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

Scientific reports
This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential drugs using bioinformatics and machine learning. Datasets for HIV (GSE 37250) and monkeypox (GSE 2412...