Konu "Machine learning" için PubMed İndeksli Yayınlar Koleksiyonu listeleme
Toplam kayıt 6, listelenen: 1-6
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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 ... -
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
(PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021)A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high ... -
Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020)The accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For ... -
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 ... -
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 ... -
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 ...