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Improved prediction of transcription binding sites from chromatin modification data

In this paper we apply machine learning to the task of predicting transcription factor binding sites by combining information on …

Kengo Sato, Tom Whitington, Timothy L. Bailey, Paul Horton

Stem Kernels for RNA Sequence Analyses

Several computational methods based on stochastic context-free grammars have been developed for modeling and analyzing functional RNA …

Yasubumi Sakakibara, Kiyoshi Asai, Kengo Sato

Preferential Presentation of Japanese Near-synonyms using Definition Statements

This paper proposes a new method of ranking near-synonyms ordered by their suitability of nuances in a particular context. Our method …

Hiroyuki Okamoto, Kengo Sato, Hiroaki Saito

Extracting Word Sequence Correspondences with Support Vector Machines

This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support …

Kengo Sato, Hiroaki Saito

Maximum Entropy Model Learning of the Translation Rules

Kengo Sato, Masakazu Nakanishi

Segmenting Sentences into Linky Strings Using D-bigram Statistics

It is obvious that segmentation takes an important role in natural language processing(NLP), especially for the languages whose …

Shiho Nobesawa, Junya Tsutsumi, Sun Da Jiang, Tomohisa Sano, Kengo Sato, Masakazu Nakanishi