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PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
(BMC, 2023)
BackgroundCell homeostasis relies on the concerted actions of genes, and dysregulated genes can lead to diseases. In living organisms, genes or their products do not act alone but within networks. Subsets of these networks ...
NeRNA: A negative data generation framework for machine learning applications of noncoding RNAs
(PERGAMON-ELSEVIER SCIENCE, 2023)
Many supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to
classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of
known ...
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)
Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ...
Topological feature generation for link prediction in biological networks
(PEERJ INC, 2023)
Graph or network embedding is a powerful method for extracting missing or
potential information from interactions between nodes in biological networks. Graph
embedding methods learn representations of nodes and interactions ...