Papers › NASCUP: Nucleic Acid Sequence Classification by Universal Probability
NASCUP: Nucleic Acid Sequence Classification by Universal Probability
Sunyoung Kwon, Gyuwan Kim, Byunghan Lee, Jongsik Chun, Sungroh Yoon, Young-Han Kim
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Motivated by the need for fast and accurate classification of unlabeled nucleotide sequences on a large scale, we developed NASCUP, a new classification method that captures statistical structures of nucleotide sequences by compact context-tree models and universal probability from information theory. NASCUP achieved BLAST-like classification accuracy consistently for several large-scale databases in orders-of-magnitude reduced runtime, and was applied to other bioinformatics tasks such as outlier detection and synthetic sequence generation.
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