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Systems driven by random functions, Wiener-Khinchine theorem.
Continuous movement of micrometre-scale particles and organisms in liquid driven by random collisions with water molecules.
An autonomous DNA motor whose propulsion was driven by random polymerization has been synthesized.
We developed a data-mining method driven by the Random Forest algorithm to model SMAD transcriptional modules in the target sequences.
However, the maximum accuracy achieved by random forests was even higher, reaching 78.95%.
A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%.
Even when the distributions of weights estimated by random forests and logistic regression in our simulations were comparable (both with a number of large weights), trimming substantially improved logistic regression but not random forests (which performed well without trimming).
In particular, the non-linearity of the data was well modeled by random forests.
We combined sequence and structure features, and selected the most important features by random forests.
A perfect score is achieved by random forests for all the datasets apart from the image-only original dataset.
Twelve bacterial genera were identified by random forest classification whose relative abundance in 13C amplicon libraries was significantly positively correlated with 13C-enrichment of DNA (Table S7).
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