Random forest

A discriminative method for protein remote homology detection based on N-Gram

S. Xie, Li, P., Jiang, Y., and Zhao, Y., A discriminative method for protein remote homology detection based on N-Gram, vol. 14, pp. 69-78, 2015.

Protein remote homology detection refers to detecting structural homology in proteins with an extremely low rate of sequence similarity. Such detection is primarily conducted using 3 methods: pairwise sequence comparisons, generative models for protein families, and discriminative classifiers. In this study, a discriminative classification method involving N-Grams was adopted to extract features using a random forest algorithm to classify data sets.

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