Machine learning for clinical decision support in infectious diseases: a narrative review of current applications
Background Machine learning (ML) is a growing field in medicine. This narrative review
describes the current body of literature on ML for clinical decision support in infectious …
describes the current body of literature on ML for clinical decision support in infectious …
A review on computational systems biology of pathogen–host interactions
Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host
interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to …
interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to …
DeNovo: virus-host sequence-based protein–protein interaction prediction
Motivation Can we predict protein–protein interactions (PPIs) of a novel virus with its host?
Three major problems arise: the lack of known PPIs for that virus to learn from, the cost of …
Three major problems arise: the lack of known PPIs for that virus to learn from, the cost of …
Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes
Metagenomic and metatranscriptomic sequencing approaches are more frequently being
used to link microbiota to important diseases and ecological changes. Many analyses have …
used to link microbiota to important diseases and ecological changes. Many analyses have …
Prediction of interactions between viral and host proteins using supervised machine learning methods
Background Viral-host protein-protein interaction plays a vital role in pathogenesis, since it
defines viral infection of the host and regulation of the host proteins. Identification of key viral …
defines viral infection of the host and regulation of the host proteins. Identification of key viral …
Comparative interactomics for virus–human protein–protein interactions: DNA viruses versus RNA viruses
Viruses are obligatory intracellular pathogens and completely depend on their hosts for
survival and reproduction. The strategies adopted by viruses to exploit host cell processes …
survival and reproduction. The strategies adopted by viruses to exploit host cell processes …
Systematic evaluation of machine learning methods for identifying human–pathogen protein–protein interactions
In recent years, high-throughput experimental techniques have significantly enhanced the
accuracy and coverage of protein–protein interaction identification, including human …
accuracy and coverage of protein–protein interaction identification, including human …
A new framework for host-pathogen interaction research
H Yu, L Li, A Huffman, J Beverley, J Hur… - Frontiers in …, 2022 - frontiersin.org
COVID-19 often manifests with different outcomes in different patients, highlighting the
complexity of the host-pathogen interactions involved in manifestations of the disease at the …
complexity of the host-pathogen interactions involved in manifestations of the disease at the …
Targeting virus-host protein interactions: Feature extraction and machine learning approaches
N Zheng, K Wang, W Zhan, L Deng - Current drug metabolism, 2019 - ingentaconnect.com
Background: Targeting critical viral-host Protein-Protein Interactions (PPIs) has enormous
application prospects for therapeutics. Using experimental methods to evaluate all possible …
application prospects for therapeutics. Using experimental methods to evaluate all possible …
Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions
Background H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are
essential for understanding the infection mechanism of the formidable pathogen M …
essential for understanding the infection mechanism of the formidable pathogen M …