AIMC Topic: Computational Biology

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Predicting drug combination side effects based on a metapath-based heterogeneous graph neural network.

BMC bioinformatics Jan 15, 2025
In recent years, combined drug screening has played a very important role in modern drug discovery. Generally, synergistic drug combinations are crucial in treatment for many diseases. However, the toxic side effects of drug combinations are probably...
Drug-Related Side Effects and Adverse Reactions Computational Biology Graph Neural Networks Drug Combinations Neural Networks, Computer Algorithms Humans Drug Discovery
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Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods.

BMC medical informatics and decision making Jan 14, 2025
BACKGROUND: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA.  METHODS: In this study, di...
Computational Biology Alopecia Areata Humans Machine Learning Biomarkers Gene Expression Profiling
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MMFuncPhos: A Multi-Modal Learning Framework for Identifying Functional Phosphorylation Sites and Their Regulatory Types.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jan 13, 2025
Protein phosphorylation plays a crucial role in regulating a wide range of biological processes, and its dysregulation is strongly linked to various diseases. While many phosphorylation sites have been identified so far, their functionality and regul...
Deep Learning Computational Biology Humans Phosphorylation
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Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms.

Scientific reports Jan 13, 2025
Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribution of immune dysregulation to PE is not fully understood, highlighting the need to explore molecul...
Humans Machine Learning Algorithms Biomarkers Pre-Eclampsia Pregnancy Gene Expression Profiling Computational Biology Female
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MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.

BMC bioinformatics Jan 13, 2025
BACKGROUND: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experi...
Graph Neural Networks Deep Learning Computational Biology MicroRNAs Small Molecule Libraries Humans Neural Networks, Computer
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Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

Sleep & breathing = Schlaf & Atmung Jan 13, 2025
BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA,...
Machine Learning Biomarkers Male Humans Sleep Apnea, Obstructive Computational Biology Diabetes Mellitus
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DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks.

BMC bioinformatics Jan 13, 2025
Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate identification can significantly expedite the process. Numerous DTI prediction methods have emerged, yet many fail to fully harness the feature informat...
Principal Component Analysis Neural Networks, Computer Humans Drug Discovery Algorithms Computational Biology
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GRL-PUL: predicting microbe-drug association based on graph representation learning and positive unlabeled learning.

Molecular omics Jan 13, 2025
Extensive research has confirmed the widespread presence of microorganisms in the human body and their crucial impact on human health, with drugs being an effective method of regulation. Hence it is essential to identify potential microbe-drug associ...
Machine Learning Algorithms Computational Biology Humans
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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.

Frontiers in cellular and infection microbiology Jan 13, 2025
INTRODUCTION: This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis.
Proteomics Enzyme-Linked Immunosorbent Assay Computational Biology Brucellosis Female Adult Humans Machine Learning Proteome Male Algorithms Middle Aged Biomarkers
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UniAMP: enhancing AMP prediction using deep neural networks with inferred information of peptides.

BMC bioinformatics Jan 11, 2025
Antimicrobial peptides (AMPs) have been widely recognized as a promising solution to combat antimicrobial resistance of microorganisms due to the increasing abuse of antibiotics in medicine and agriculture around the globe. In this study, we propose ...
Deep Learning Computational Biology Neural Networks, Computer Antimicrobial Peptides
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