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Predicting bacterial functional traits from whole genome sequences using random forest. Abstract: Microbes are the most abundant and diverse biota on earth ...
Conference PaperPDF Available. Predicting bacterial functional traits from whole genome sequences using random forest ... using random forest,” BMC.
We then applied a Random Forest (RF) algorithm [7] for the regression problem to understand relationships between genetic sequences and continuous functional ...
Predicting bacterial functional traits from whole genome sequences using random forest · Wei Zhang, Erliang Zeng, +3 authors. Stuart E. Jones · Published in ...
Dec 19, 2023 · Random forest classification using gene presence/absence predicts traits by exploiting phylogenetic correlations. (A) The genome similarity ...
Jan 30, 2024 · Our machine learning models predicted sub-species virulence potential with nested cross-validation F1-scores up to 0.88 for the majority voting ...
Dec 24, 2021 · Subsequently, we applied the ML random forest (RF) algorithm to the allelic variation of the TRs to predict six metadata traits of the genomes ...
Missing: functional | Show results with:functional
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Jun 16, 2021 · Our work stands as template for predicting other untested GAS genomic traits using RF and RR allele types. Given the accuracy of the ...
Oct 6, 2021 · (2018) analyzed AMR using different machine learning algorithms [e.g. support vector machine (SVM), logistic regression (LR) and random forest ( ...
Mar 7, 2024 · To predict the lifestyle of non-annotated genomes, we trained and tested a random forest machine learning model with the gene cluster absence/ ...
Missing: whole | Show results with:whole