NASCUP: Nucleic Acid Sequence Classification by Universal Probability

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Publication date: 16 November 2015

Abstract: 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.

Has companion code repository: https://github.com/nascup/nascup

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