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microBiomeGSM: the identification of taxonomic biomarkers from metagenomic data using grouping, scoring and modeling (G-S-M) approach
(FRONTIERS MEDIA SA, 2023)
Numerous biological environments have been characterized with the advent of metagenomic sequencing using next generation sequencing which lays out the relative abundance values of microbial taxa. Modeling the human microbiome ...
Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME
(F1000 Research, 2020)
In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over ...
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
Human gut microbiota is a complex community of organisms including trillions of bacteria. While these microorganisms are considered as essential regulators of our immune system, some of them can cause several diseases. In ...
miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
(Frontiers Media S.A., 2023)
During recent years, biological experiments and increasing evidence have shown that microRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex ...