Leveraging artificial intelligence in the fight against infectious diseases
Despite advances in molecular biology, genetics, computation, and medicinal chemistry,
infectious disease remains an ominous threat to public health. Addressing the challenges …
infectious disease remains an ominous threat to public health. Addressing the challenges …
Emerging and reemerging infectious diseases: global trends and new strategies for their prevention and control
S Wang, W Li, Z Wang, W Yang, E Li, X **a… - Signal transduction and …, 2024 - nature.com
To adequately prepare for potential hazards caused by emerging and reemerging infectious
diseases, the WHO has issued a list of high-priority pathogens that are likely to cause future …
diseases, the WHO has issued a list of high-priority pathogens that are likely to cause future …
iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate
understanding of the sequence (-structure)-function paradigm for DNAs, RNAs and proteins …
understanding of the sequence (-structure)-function paradigm for DNAs, RNAs and proteins …
Learning spatial structures of proteins improves protein–protein interaction prediction
Spatial structures of proteins are closely related to protein functions. Integrating protein
structures improves the performance of protein–protein interaction (PPI) prediction …
structures improves the performance of protein–protein interaction (PPI) prediction …
Positive-unlabeled learning in bioinformatics and computational biology: a brief review
Conventional supervised binary classification algorithms have been widely applied to
address significant research questions using biological and biomedical data. This …
address significant research questions using biological and biomedical data. This …
Machine learning on protein–protein interaction prediction: models, challenges and trends
Protein–protein interactions (PPIs) carry out the cellular processes of all living organisms.
Experimental methods for PPI detection suffer from high cost and false-positive rate, hence …
Experimental methods for PPI detection suffer from high cost and false-positive rate, hence …
Holistic one health surveillance framework: synergizing environmental, animal, and human determinants for enhanced infectious disease management
Recent pandemics, including the COVID-19 outbreak, have brought up growing concerns
about transmission of zoonotic diseases from animals to humans. This highlights the …
about transmission of zoonotic diseases from animals to humans. This highlights the …
Graph neural network for protein–protein interaction prediction: a comparative study
H Zhou, W Wang, J **, Z Zheng, B Zhou - Molecules, 2022 - mdpi.com
Proteins are the fundamental biological macromolecules which underline practically all
biological activities. Protein–protein interactions (PPIs), as they are known, are how proteins …
biological activities. Protein–protein interactions (PPIs), as they are known, are how proteins …
[HTML][HTML] Artificial intelligence approaches to human-microbiome protein–protein interactions
Host-microbiome interactions play significant roles in human health and disease. Artificial
intelligence approaches have been developed to better understand and predict the …
intelligence approaches have been developed to better understand and predict the …
NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction
The prediction of genes related to diseases is important to the study of the diseases due to
high cost and time consumption of biological experiments. Network propagation is a popular …
high cost and time consumption of biological experiments. Network propagation is a popular …