Programming in Modal Logic: An Extension of PROLOG based on Modal Logic. - Yasubumi Sakakibara (LP, 1986)

An Efficient Learning of Context-Free Grammars for Bottom-Up Parsers. - Yasubumi Sakakibara (FGCS, 1988)

Occam Algorithms for Learning From Noisy Examples. - Yasubumi Sakakibara (ALT, 1990)

Exact Learning of Semilinear Sets. - Yuji Takada; Kunihiko Hiraishi; Yasubumi Sakakibara (ALT, 1990)

Inductive inference of logic programs based on algebraic semantics. - Yasubumi Sakakibara (New Gener. Comput., 1990)

Learning Context-Free Grammars from Structural Data in Polynomial Time. - Yasubumi Sakakibara (Theor. Comput. Sci., 1990)

ACE: A syntax-directed editor customizable from examples and queries. - Yuji Takada; Yasubumi Sakakibara; Takeshi Ohtani (ALT, 1991)

On Learning from Queries and Counterexamples in the Presence of Noise. - Yasubumi Sakakibara (Inf. Process. Lett., 1991)

A Noise Model on Learning Sets of Strings. - Yasubumi Sakakibara; Rani Siromoney (COLT, 1992)

Efficient Learning of Context-Free Grammars from Positive Structural Examples - Yasubumi Sakakibara (Inf. Comput., 1992)

Noise-Tolerant Occam Algorithms and Their Applications to Learning Decision Trees. - Yasubumi Sakakibara (Mach. Learn., 1993)

Learning Languages by Collecting Cases and Tuning Parameters. - Yasubumi Sakakibara; Klaus P. Jantke; Steffen Lange (AII/ALT, 1994)

Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars. - Yasubumi Sakakibara; Michael Brown; Richard Hughey; I. Saira Mian; Kimmen Sjölander; Rebecca C. Underwood; David Haussler (CPM, 1994)

Stochastic Context-Free Grammars for Modeling RN. - Yasubumi Sakakibara; Michael Brown; Rebecca C. Underwood; I. Saira Mian; David Haussler (HICSS (5), 1994)

Grammatical Inference: An Old and New Paradigm. - Yasubumi Sakakibara (ALT, 1995)

Simple recurrent networks as generalized hidden Markov models with distributed representations. - Yasubumi Sakakibara; Mostefa Golea (ICNN, 1995)

Stochastic simple recurrent neural networks. - Mostefa Golea; Masahiro Matsuoka; Yasubumi Sakakibara (ICGI, 1996)

A machine learning approach to knowledge acquisitions from text databases. - Yasubumi Sakakibara; Kazuo Misue; Takeshi Koshiba (Int. J. Hum. Comput. Interact., 1996)

On Case Based Learnability of Language. - Christoph Globig; Klaus P. Jantke; Steffen Lange; Yasubumi Sakakibara (New Gener. Comput., 1997)

Recent Advances of Grammatical Inference. - Yasubumi Sakakibara (Theor. Comput. Sci., 1997)

GA-based Learning of Context-Free Grammars using Tabular Representations. - Yasubumi Sakakibara; Mitsuhiro Kondo (ICML, 1999)

Splicing on Tree-Like Structures. - Yasubumi Sakakibara; Claudio Ferretti (Theor. Comput. Sci., 1999)

Solving Computational Learning Problems of Boolean Formulae on DNA Computers. - Yasubumi Sakakibara (DNA Computing, 2000)

Learning Context-Free Grammars from Partially Structured Examples. - Yasubumi Sakakibara; Hidenori Muramatsu (ICGI, 2000)

Approximate identification of finite elasticity. - Satoshi Kobayashi; Yasubumi Sakakibara; Takashi Yokomori (Where Mathematics, Computer Science, Linguistics and Biology Meet, 2001)

Probabilistic logical inference using quantities of DNA strands. - Yasubumi Sakakibara (CEC, 2001)

Population Computation and Majority Inference in Test Tube. - Yasubumi Sakakibara (DNA, 2001)

Sticker systems with complex structures. - Yasubumi Sakakibara; Satoshi Kobayashi (Soft Comput., 2001)

Multiple splicing systems and the universal computability. - Satoshi Kobayashi; Yasubumi Sakakibara (Theor. Comput. Sci., 2001)

A Magic Pot : Self-assembly Computation Revisited. - Takashi Yokomori; Yasubumi Sakakibara; Satoshi Kobayashi (Formal and Natural Computing, 2002)

A DNA-based Computational Model Using a Specific Type of Restriction Enzyme. - Yasubumi Sakakibara; Hiroshi Imai (DNA, 2002)

In Vitro Translation-Based Computations. - Yasubumi Sakakibara; Takahiro Hohsaka (DNA, 2003)

Pair hidden Markov models on tree structures. - Yasubumi Sakakibara (ISMB (Supplement of Bioinformatics), 2003)

DNA-based algorithms for learning Boolean formulae. - Yasubumi Sakakibara (Nat. Comput., 2003)

An Algorithm for Testing Structure Freeness of Biomolecular Sequences. - Satoshi Kobayashi; Takashi Yokomori; Yasubumi Sakakibara (Aspects of Molecular Computing, 2004)

A DNA-Based Computational Model Using a Specific Type of Restriction Enzymes. - Yasubumi Sakakibara; Hiroshi Imai (J. Autom. Lang. Comb., 2004)

Discriminative Discovery of Transcription Factor Binding Sites from Location Data. - Yuji Kawada; Yasubumi Sakakibara (CSB, 2005)

Intensive In Vitro Experiments of Implementing and Executing Finite Automata in Test Tube. - Junna Kuramochi; Yasubumi Sakakibara (DNA, 2005)

Development of an In Vivo Computer Based on Escherichia coli. - Hirotaka Nakagawa; Kensaku Sakamoto; Yasubumi Sakakibara (DNA, 2005)

RNA secondary structural alignment with conditional random fields. - Kengo Sato; Yasubumi Sakakibara (ECCB/JBI, 2005)

Pair stochastic tree adjoining grammars for aligning and predicting pseudoknot RNA structures. - Hiroshi Matsui; Kengo Sato; Yasubumi Sakakibara (Bioinform., 2005)

Development of a Bacteria Computer: From in silico Finite Automata to in virto AND in vivo. - Yasubumi Sakakibara (Bull. EATCS, 2005)

Grammatical Inference in Bioinformatics. - Yasubumi Sakakibara (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

Learning context-free grammars using tabular representations. - Yasubumi Sakakibara (Pattern Recognit., 2005)

Discriminative Detection of Cis-Acting Regulatory Variation From Location Data. - Yuji Kawada; Yasubumi Sakakibara (APBC, 2006)

Implementing in vivo Cellular Automata using Toggle Switch and Inter-Bacteria Communication Mechanism. - Yasubumi Sakakibara; Hirotaka Nakagawa; Yusaku Nakashima; Katsuyuki Yugi (BIONETICS, 2007)

Stem Kernels for RNA Sequence Analyses. - Yasubumi Sakakibara; Kiyoshi Asai; Kengo Sato (BIRD, 2007)

Probabilistic Inference in Test Tube and its Application to Gene Expression Profiles. - Yasubumi Sakakibara; Takashi Yokomori; Satoshi Kobayashi; Akira Suyama (Formal Models, Languages and Applications, 2007)

Statistical prediction of protein-chemical interactions based on chemical structure and mass spectrometry data. - Nobuyoshi Nagamine; Yasubumi Sakakibara (Bioinform., 2007)

Stem Kernels for RNA Sequence Analyses. - Yasubumi Sakakibara; Kris Popendorf; Nana Ogawa; Kiyoshi Asai; Kengo Sato (J. Bioinform. Comput. Biol., 2007)

Guest editorial to the special issue on grammatical inference. - Georgios Paliouras; Yasubumi Sakakibara (Mach. Learn., 2007)

Bio-Molecular Computing of Finite-State Machine. - Yasubumi Sakakibara (BIONETICS, 2008)

Directed acyclic graph kernels for structural RNA analysis. - Kengo Sato; Toutai Mituyama; Kiyoshi Asai; Yasubumi Sakakibara (BMC Bioinform., 2008)

Software.ncrna.org: web servers for analyses of RNA sequences. - Kiyoshi Asai; Hisanori Kiryu; Michiaki Hamada; Yasuo Tabei; Kengo Sato; Hiroshi Matsui; Yasubumi Sakakibara; Goro Terai; Toutai Mituyama (Nucleic Acids Res., 2008)

Sequence and Structural Analyses for Functional Non-coding RNAs. - Yasubumi Sakakibara; Kengo Sato (Algorithmic Bioprocesses, 2009)

Accurate identification of orthologous segments among multiple genomes. - Tsuyoshi Hachiya; Yasunori Osana; Kris Popendorf; Yasubumi Sakakibara (Bioinform., 2009)

Support Vector Machine Prediction of N- and O-glycosylation Sites Using Whole Sequence Information and Subcellular Localization. - Kenta Sasaki; Nobuyoshi Nagamine; Yasubumi Sakakibara (Inf. Media Technol., 2009)

Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening. - Nobuyoshi Nagamine; Takayuki Shirakawa; Yusuke Minato; Kentaro Torii; Hiroki Kobayashi; Masaya Imoto; Yasubumi Sakakibara (PLoS Comput. Biol., 2009)

Development of a Bacteria Computer: From in silico Finite Automata to in vitro and in vivo. - Yasubumi Sakakibara (CiE, 2010)

Improvement of Structure Conservation Index with Centroid Estimators. - Yohei Okada; Kengo Sato; Yasubumi Sakakibara (Pacific Symposium on Biocomputing, 2010)

Robust and accurate prediction of noncoding RNAs from aligned sequences. - Yutaka Saito; Kengo Sato; Yasubumi Sakakibara (BMC Bioinform., 2010)

A Non-Parametric Bayesian Approach for Predicting RNA Secondary Structures. - Kengo Sato; Michiaki Hamada; Toutai Mituyama; Kiyoshi Asai; Yasubumi Sakakibara (J. Bioinform. Comput. Biol., 2010)

Operon structure optimization by random self-assembly. - Yusuke Nakagawa; Katsuyuki Yugi; Kenji Tsuge; Mitsuhiro Itaya; Hiroshi Yanagawa; Yasubumi Sakakibara (Nat. Comput., 2010)

Probabilistic Context-Free Grammars. - Yasubumi Sakakibara (Encyclopedia of Machine Learning, 2010)

MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. - Toshiaki Namiki; Tsuyoshi Hachiya; Hideaki Tanaka; Yasubumi Sakakibara (BCB, 2011)

Fast and accurate clustering of noncoding RNAs using ensembles of sequence alignments and secondary structures. - Yutaka Saito; Kengo Sato; Yasubumi Sakakibara (BMC Bioinform., 2011)

Poster: In silico microarray algorithm: Accurate and fast taxonomic profiling from short read sequences. - Tomoya Tagami; Tsuyoshi Hachiya; Yasubumi Sakakibara (ICCABS, 2012)

SAMSCOPE: an OpenGL-based real-time interactive scale-free SAM viewer. - Kris Popendorf; Yasubumi Sakakibara (Bioinform., 2012)

COPICAT: a software system for predicting interactions between proteins and chemical compounds. - Yasubumi Sakakibara; Tsuyoshi Hachiya; Miho Uchida; Nobuyoshi Nagamine; Yohei Sugawara; Masahiro Yokota; Masaomi Nakamura; Kris Popendorf; Takashi Komori; Kengo Sato (Bioinform., 2012)

DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition. - Kengo Sato; Yuki Kato; Tatsuya Akutsu; Kiyoshi Asai; Yasubumi Sakakibara (Bioinform., 2012)

An efficient algorithm for de novo predictions of biochemical pathways between chemical compounds. - Masaomi Nakamura; Tsuyoshi Hachiya; Yutaka Saito; Kengo Sato; Yasubumi Sakakibara (BMC Bioinform., 2012)

Foreword. - Yasubumi Sakakibara; Yongli Mi (Nat. Comput., 2012)

Bacterial Computing and Molecular Communication. - Yasubumi Sakakibara; Satoshi Hiyama (Handbook of Natural Computing, 2012)

A Machine Learning Based Approach to de novo Sequencing of Glycans from Tandem Mass Spectrometry Spectrum. - Shotaro Kumozaki; Kengo Sato; Yasubumi Sakakibara (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing. - Mariko Tsuchiya; Kojiro Amano; Masaya Abe; Misato Seki; Sumitaka Hase; Kengo Sato; Yasubumi Sakakibara (Bioinform., 2016)

Probabilistic Context-Free Grammars. - Yasubumi Sakakibara (Encyclopedia of Machine Learning and Data Mining, 2017)

Convolutional neural networks for classification of alignments of non-coding RNA sequences. - Genta Aoki; Yasubumi Sakakibara (Bioinform., 2018)

Convolutional neural network based on SMILES representation of compounds for detecting chemical motif. - Maya Hirohara; Yutaka Saito; Yuki Koda; Kengo Sato; Yasubumi Sakakibara (BMC Bioinform., 2018)

A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model. - Manato Akiyama; Kengo Sato; Yasubumi Sakakibara (J. Bioinform. Comput. Biol., 2018)

Comprehensive evaluation of non-hybrid genome assembly tools for third-generation PacBio long-read sequence data. - Vasanthan Jayakumar; Yasubumi Sakakibara (Briefings Bioinform., 2019)

Guest Editorial for the 16th Asia Pacific Bioinformatics Conference. - Yoshihiro Yamanishi; Yasubumi Sakakibara; Yi-Ping Phoebe Chen (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly. - Kuo-Ching Liang; Yasubumi Sakakibara (BMC Bioinform., 2021)

Deep learning integration of molecular and interactome data for protein-compound interaction prediction. - Narumi Watanabe; Yuuto Ohnuki; Yasubumi Sakakibara (J. Cheminformatics, 2021)

Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition. - Kaito Kishi; Takahiko Satoh; Rudy Raymond; Naoki Yamamoto; Yasubumi Sakakibara (IEEE J. Emerg. Sel. Topics Circuits Syst., 2022)

Deep learning of multimodal networks with topological regularization for drug repositioning. - Yuto Ohnuki; Manato Akiyama; Yasubumi Sakakibara (J. Cheminformatics, 2024)