Base-pairing profile local alignment kernels for functional RNA analyses

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概要

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• We have recently proposed novel kernel functions, called base-pairing profile local alignment (BPLA) kernels for discrimination and detection of functional RNA sequences using SVMs. We employ STRAL's scoring function which takes into account sequence similarities as well as upstream and downstream basepairing probabilities, which enables us to model secondary structures of RNA sequences. In this paper, we develop a method for optimizing hyperparameters of BPLA kernels with respect to discrimination accuracy using a gradient-based optimization technique. Our experiments show that the proposed method can find a nearly optimal set of parameters much faster than the grid search on all parameter combinations.

• 2009-05-18

著者

• Kengo Sato

  Graduate School Of Frontier Sciences University Of Tokyo

• Yasubumi Sakakibara

  慶應義塾大学理工学部生命情報学科

• Kengo Sato

  (社) バイオ産業情報化コンソーシアム|(独) 産業技術総合研究所生命情報工学研究センター|慶應義塾大学理工学部生命情報学科

• Yutaka Saito

  慶應義塾大学理工学部生命情報学科

関連論文

• RNA-RNA Interaction Prediction Using Integer Programming with Threshold Cut
• Base-pairing profile local alignment kernels for functional RNA analyses
• A Modified Genovo Metagenome Assembler for 454 Paired End Reads

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