AIMC Topic: Computational Biology

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A Systematic Review of the Application of Graph Neural Networks to Extract Candidate Genes and Biological Associations.

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
The development of high throughput technologies has resulted in the collection of large quantities of genomic and transcriptomic data. However, identifying disease-associated genes or networks from these data has remained an ongoing challenge. In rec...

PFHxA and PFHxS promote breast cancer progression in 3D culture: MEX3C-associated immune infiltration revealed by bioinformatics and machine learning.

Journal of hazardous materials
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with widespread use and bioaccumulative potential. Short-chain PFAS such as perfluorohexanoic acid (PFHxA) and perfluorohexane sulfonate (PFHxS) have been introduced...

Identification of pyroptosis-related gene S100A12 as a potential diagnostic biomarker for sepsis through bioinformatics analysis and machine learning.

Molecular immunology
Sepsis is a non-discriminatory inflammatory reaction that can result in a diverse array of organ dysfunctions, which can be fatal. Pyroptosis is a programmed mechanism of cell death that is distinguishable from apoptosis and other forms of cellular d...

Accurate identification and mechanistic evaluation of pathogenic missense variants with .

Proceedings of the National Academy of Sciences of the United States of America
Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here , a machine learning too...

ProFun-SOM: Protein Function Prediction for Specific Ontology Based on Multiple Sequence Alignment Reconstruction.

IEEE transactions on neural networks and learning systems
Protein function prediction is crucial for understanding species evolution, including viral mutations. Gene ontology (GO) is a standardized representation framework for describing protein functions with annotated terms. Each ontology is a specific fu...

Integration of Bioinformatics and Machine Learning Strategies Identifies Ferroptosis and Immune Infiltration Signatures in Peri-Implantitis.

International journal of molecular sciences
Peri-implantitis (PI) is a chronic inflammatory disease that ultimately leads to the dysfunction and loss of implants with established osseointegration. Ferroptosis has been implicated in the progression of PI, but its precise mechanisms remain uncle...

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.

Scientific reports
Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive understanding of the mechanism is lacking. This work aimed to pinpoint distinctive anoikis-related genes (A...

Artificial-intelligence-driven Innovations in Mechanistic Computational Modeling and Digital Twins for Biomedical Applications.

Journal of molecular biology
Understanding of complex biological systems remains a significant challenge due to their high dimensionality, nonlinearity, and context-specific behavior. Artificial intelligence (AI) and mechanistic modeling are becoming essential tools for studying...

AdptDilatedGCN: Protein-ligand binding affinity prediction based on multi-scale interaction fusion mechanism and dilated GCN.

International journal of biological macromolecules
Predicting protein-ligand binding affinity is crucial for drug discovery. However, existing prediction methods often make insufficient use of the features of proteins and ligands, lack interactions between different information, and have difficulty i...

Massive experimental quantification allows interpretable deep learning of protein aggregation.

Science advances
Protein aggregation is a pathological hallmark of more than 50 human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experi...