Drug combinations: a strategy to extend the life of antibiotics in the 21st century
Antimicrobial resistance threatens a resurgence of life-threatening bacterial infections and
the potential demise of many aspects of modern medicine. Despite intensive drug discovery …
the potential demise of many aspects of modern medicine. Despite intensive drug discovery …
Exploiting machine learning for end-to-end drug discovery and development
A variety of machine learning methods such as naive Bayesian, support vector machines
and more recently deep neural networks are demonstrating their utility for drug discovery …
and more recently deep neural networks are demonstrating their utility for drug discovery …
Machine learning for antimicrobial resistance prediction: current practice, limitations, and clinical perspective
Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern
medicine. Effective prevention strategies are urgently required to slow the emergence and …
medicine. Effective prevention strategies are urgently required to slow the emergence and …
Alignment-free sequence comparison: benefits, applications, and tools
Alignment-free sequence analyses have been applied to problems ranging from whole-
genome phylogeny to the classification of protein families, identification of horizontally …
genome phylogeny to the classification of protein families, identification of horizontally …
Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella
Nontyphoidal Salmonella species are the leading bacterial cause of foodborne disease in
the United States. Whole-genome sequences and paired antimicrobial susceptibility data …
the United States. Whole-genome sequences and paired antimicrobial susceptibility data …
Emerging applications of machine learning in food safety
Food safety continues to threaten public health. Machine learning holds potential in
leveraging large, emerging data sets to improve the safety of the food supply and mitigate …
leveraging large, emerging data sets to improve the safety of the food supply and mitigate …
Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases
In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
Develo** an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae
Antimicrobial resistant infections are a serious public health threat worldwide. Whole
genome sequencing approaches to rapidly identify pathogens and predict antibiotic …
genome sequencing approaches to rapidly identify pathogens and predict antibiotic …
Artificial intelligence for antimicrobial resistance prediction: challenges and opportunities towards practical implementation
Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It
is very important to understand and apply effective strategies to counter the impact of AMR …
is very important to understand and apply effective strategies to counter the impact of AMR …
Interpretable genotype-to-phenotype classifiers with performance guarantees
Understanding the relationship between the genome of a cell and its phenotype is a central
problem in precision medicine. Nonetheless, genotype-to-phenotype prediction comes with …
problem in precision medicine. Nonetheless, genotype-to-phenotype prediction comes with …