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2020 – today
- 2024
[j46]Yuto Ohnuki, Manato Akiyama, Yasubumi Sakakibara:
Deep learning of multimodal networks with topological regularization for drug repositioning. J. Cheminformatics 16(1): 103 (2024)- 2022
- [j45]Kaito Kishi, Takahiko Satoh
, Rudy Raymond, Naoki Yamamoto, Yasubumi Sakakibara:
Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(3): 602-613 (2022) - 2021
- [j44]Kuo-Ching Liang, Yasubumi Sakakibara:
MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly. BMC Bioinform. 22-S(6): 427 (2021) - [j43]Narumi Watanabe, Yuuto Ohnuki, Yasubumi Sakakibara:
Deep learning integration of molecular and interactome data for protein-compound interaction prediction. J. Cheminformatics 13(1): 36 (2021)
2010 – 2019
- 2019
- [j42]Vasanthan Jayakumar, Yasubumi Sakakibara:
Comprehensive evaluation of non-hybrid genome assembly tools for third-generation PacBio long-read sequence data. Briefings Bioinform. 20(3): 866-876 (2019) - [j41]Yoshihiro Yamanishi, Yasubumi Sakakibara, Yi-Ping Phoebe Chen:
Guest Editorial for the 16th Asia Pacific Bioinformatics Conference. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 1-2 (2019) - 2018
- [j40]Genta Aoki, Yasubumi Sakakibara:
Convolutional neural networks for classification of alignments of non-coding RNA sequences. Bioinform. 34(13): i237-i244 (2018) - [j39]Maya Hirohara, Yutaka Saito, Yuki Koda, Kengo Sato, Yasubumi Sakakibara:
Convolutional neural network based on SMILES representation of compounds for detecting chemical motif. BMC Bioinform. 19-S(19): 83-94 (2018) - [j38]Manato Akiyama, Kengo Sato, Yasubumi Sakakibara:
A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model. J. Bioinform. Comput. Biol. 16(6): 1840025:1-1840025:15 (2018) - 2017
- [r2]Yasubumi Sakakibara:
Probabilistic Context-Free Grammars. Encyclopedia of Machine Learning and Data Mining 2017: 1013-1017 - 2016
- [j37]Mariko Tsuchiya, Kojiro Amano, Masaya Abe, Misato Seki, Sumitaka Hase, Kengo Sato, Yasubumi Sakakibara:
SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing. Bioinform. 32(12): 369-377 (2016) - 2015
- [j36]Shotaro Kumozaki, Kengo Sato, Yasubumi Sakakibara:
A Machine Learning Based Approach to de novo Sequencing of Glycans from Tandem Mass Spectrometry Spectrum. IEEE ACM Trans. Comput. Biol. Bioinform. 12(6): 1267-1274 (2015) - 2012
- [j35]Yasubumi Sakakibara, Tsuyoshi Hachiya, Miho Uchida, Nobuyoshi Nagamine, Yohei Sugawara, Masahiro Yokota, Masaomi Nakamura, Kris Popendorf, Takashi Komori, Kengo Sato:
COPICAT: a software system for predicting interactions between proteins and chemical compounds. Bioinform. 28(5): 745-746 (2012) - [j34]Kris Popendorf, Yasubumi Sakakibara:
SAMSCOPE: an OpenGL-based real-time interactive scale-free SAM viewer. Bioinform. 28(9): 1276-1277 (2012) - [j33]Kengo Sato, Yuki Kato, Tatsuya Akutsu, Kiyoshi Asai, Yasubumi Sakakibara:
DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition. Bioinform. 28(24): 3218-3224 (2012) - [j32]Masaomi Nakamura, Tsuyoshi Hachiya, Yutaka Saito, Kengo Sato, Yasubumi Sakakibara:
An efficient algorithm for de novo predictions of biochemical pathways between chemical compounds. BMC Bioinform. 13(S-17): S8 (2012) - [j31]Yasubumi Sakakibara, Yongli Mi:
Foreword. Nat. Comput. 11(2): 185-186 (2012) - [c42]Tomoya Tagami, Tsuyoshi Hachiya, Yasubumi Sakakibara:
Poster: In silico microarray algorithm: Accurate and fast taxonomic profiling from short read sequences. ICCABS 2012: 1 - [p1]Yasubumi Sakakibara, Satoshi Hiyama:
Bacterial Computing and Molecular Communication. Handbook of Natural Computing 2012: 1203-1232 - 2011
- [j30]Yutaka Saito, Kengo Sato, Yasubumi Sakakibara:
Fast and accurate clustering of noncoding RNAs using ensembles of sequence alignments and secondary structures. BMC Bioinform. 12(S-1): S48 (2011) - [c41]Toshiaki Namiki, Tsuyoshi Hachiya, Hideaki Tanaka, Yasubumi Sakakibara:
MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. BCB 2011: 116-124 - [e3]Yasubumi Sakakibara, Yongli Mi:
DNA Computing and Molecular Programming - 16th International Conference, DNA 16, Hong Kong, China, June 14-17, 2010, Revised Selected Papers. Lecture Notes in Computer Science 6518, Springer 2011, ISBN 978-3-642-18304-1 [contents] - 2010
- [j29]Yutaka Saito, Kengo Sato, Yasubumi Sakakibara:
Robust and accurate prediction of noncoding RNAs from aligned sequences. BMC Bioinform. 11(S-7): S3 (2010) - [j28]Kengo Sato, Michiaki Hamada, Toutai Mituyama, Kiyoshi Asai, Yasubumi Sakakibara:
A Non-Parametric Bayesian Approach for Predicting RNA Secondary Structures. J. Bioinform. Comput. Biol. 8(4): 727-742 (2010) - [j27]Yusuke Nakagawa, Katsuyuki Yugi, Kenji Tsuge, Mitsuhiro Itaya, Hiroshi Yanagawa, Yasubumi Sakakibara:
Operon structure optimization by random self-assembly. Nat. Comput. 9(1): 173-181 (2010) - [c40]Yasubumi Sakakibara:
Development of a Bacteria Computer: From in silico Finite Automata to in vitro and in vivo. CiE 2010: 362-371 - [c39]Yohei Okada, Kengo Sato, Yasubumi Sakakibara:
Improvement of Structure Conservation Index with Centroid Estimators. Pacific Symposium on Biocomputing 2010: 88-97 - [r1]Yasubumi Sakakibara:
Probabilistic Context-Free Grammars. Encyclopedia of Machine Learning 2010: 802-805
2000 – 2009
- 2009
- [j26]Tsuyoshi Hachiya, Yasunori Osana, Kris Popendorf, Yasubumi Sakakibara:
Accurate identification of orthologous segments among multiple genomes. Bioinform. 25(7): 853-860 (2009) - [j25]Tsuyoshi Hachiya, Yasunori Osana, Kris Popendorf, Yasubumi Sakakibara:
Accurate identification of orthologous segments among multiple genomes. Bioinform. 25(11): 1474 (2009) - [j24]Kenta Sasaki, Nobuyoshi Nagamine, Yasubumi Sakakibara:
Support Vector Machine Prediction of N- and O-glycosylation Sites Using Whole Sequence Information and Subcellular Localization. Inf. Media Technol. 4(2): 400-410 (2009) - [j23]Nobuyoshi Nagamine, Takayuki Shirakawa, Yusuke Minato, Kentaro Torii, Hiroki Kobayashi, Masaya Imoto, Yasubumi Sakakibara:
Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening. PLoS Comput. Biol. 5(6) (2009) - [c38]Yasubumi Sakakibara, Kengo Sato:
Sequence and Structural Analyses for Functional Non-coding RNAs. Algorithmic Bioprocesses 2009: 63-79 - [c37]Kengo Sato, Michiaki Hamada, Toutai Mituyama, Kiyoshi Asai, Yasubumi Sakakibara:
A Non-parametric Bayesian Approach for Predicting RNA Secondary Structures. WABI 2009: 286-297 - 2008
- [j22]Kengo Sato, Toutai Mituyama, Kiyoshi Asai, Yasubumi Sakakibara:
Directed acyclic graph kernels for structural RNA analysis. BMC Bioinform. 9 (2008) - [j21]Kiyoshi Asai, Hisanori Kiryu, Michiaki Hamada, Yasuo Tabei, Kengo Sato, Hiroshi Matsui, Yasubumi Sakakibara, Goro Terai, Toutai Mituyama:
Software.ncrna.org: web servers for analyses of RNA sequences. Nucleic Acids Res. 36(Web-Server-Issue): 75-78 (2008) - [c36]Yasubumi Sakakibara:
Bio-Molecular Computing of Finite-State Machine. BIONETICS 2008: 33 - [c35]Yusuke Nakagawa, Katsuyuki Yugi, Kenji Tsuge, Mitsuhiro Itaya, Hiroshi Yanagawa, Yasubumi Sakakibara:
Operon Structure Optimization by Random Self-assembly. DNA 2008: 33-40 - 2007
- [j20]Nobuyoshi Nagamine, Yasubumi Sakakibara:
Statistical prediction of protein-chemical interactions based on chemical structure and mass spectrometry data. Bioinform. 23(15): 2004-2012 (2007) - [j19]Yasubumi Sakakibara, Kris Popendorf, Nana Ogawa, Kiyoshi Asai, Kengo Sato:
Stem Kernels for RNA Sequence Analyses. J. Bioinform. Comput. Biol. 5(5): 1103-1122 (2007) - [j18]Georgios Paliouras, Yasubumi Sakakibara:
Guest editorial to the special issue on grammatical inference. Mach. Learn. 66(1): 3-5 (2007) - [c34]Yasubumi Sakakibara, Hirotaka Nakagawa, Yusaku Nakashima, Katsuyuki Yugi:
Implementing in vivo Cellular Automata using Toggle Switch and Inter-Bacteria Communication Mechanism. BIONETICS 2007: 322-325 - [c33]Yasubumi Sakakibara, Kiyoshi Asai, Kengo Sato:
Stem Kernels for RNA Sequence Analyses. BIRD 2007: 278-291 - [c32]Yasubumi Sakakibara, Takashi Yokomori, Satoshi Kobayashi, Akira Suyama:
Probabilistic Inference in Test Tube and its Application to Gene Expression Profiles. Formal Models, Languages and Applications 2007: 304-319 - 2006
- [c31]Yuji Kawada, Yasubumi Sakakibara:
Discriminative Detection of Cis-Acting Regulatory Variation From Location Data. APBC 2006: 89-98 - [e2]Yasubumi Sakakibara, Satoshi Kobayashi, Kengo Sato, Tetsuro Nishino, Etsuji Tomita:
Grammatical Inference: Algorithms and Applications, 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006, Proceedings. Lecture Notes in Computer Science 4201, Springer 2006, ISBN 3-540-45264-8 [contents] - 2005
- [j17]Hiroshi Matsui, Kengo Sato, Yasubumi Sakakibara:
Pair stochastic tree adjoining grammars for aligning and predicting pseudoknot RNA structures. Bioinform. 21(11): 2611-2617 (2005) - [j16]Yasubumi Sakakibara:
Development of a Bacteria Computer: From in silico Finite Automata to in virto AND in vivo. Bull. EATCS 87: 165-178 (2005) - [j15]Yasubumi Sakakibara:
Grammatical Inference in Bioinformatics. IEEE Trans. Pattern Anal. Mach. Intell. 27(7): 1051-1062 (2005) - [j14]Yasubumi Sakakibara:
Learning context-free grammars using tabular representations. Pattern Recognit. 38(9): 1372-1383 (2005) - [c30]Yuji Kawada, Yasubumi Sakakibara:
Discriminative Discovery of Transcription Factor Binding Sites from Location Data. CSB 2005: 86-89 - [c29]Junna Kuramochi, Yasubumi Sakakibara:
Intensive In Vitro Experiments of Implementing and Executing Finite Automata in Test Tube. DNA 2005: 193-202 - [c28]Hirotaka Nakagawa, Kensaku Sakamoto, Yasubumi Sakakibara:
Development of an In Vivo Computer Based on Escherichia coli. DNA 2005: 203-212 - [c27]Kengo Sato, Yasubumi Sakakibara:
RNA secondary structural alignment with conditional random fields. ECCB/JBI 2005: 242 - 2004
- [j13]Yasubumi Sakakibara, Hiroshi Imai:
A DNA-Based Computational Model Using a Specific Type of Restriction Enzymes. J. Autom. Lang. Comb. 9(1): 111-119 (2004) - [c26]Satoshi Kobayashi, Takashi Yokomori, Yasubumi Sakakibara:
An Algorithm for Testing Structure Freeness of Biomolecular Sequences. Aspects of Molecular Computing 2004: 266-277 - [c25]Hiroshi Matsui, Kengo Sato, Yasubumi Sakakibara:
Pair Stochastic Tree Adjoining Grammars for Aligning and Predicting Pseudoknot RNA Structures. CSB 2004: 290-299 - [e1]Georgios Paliouras, Yasubumi Sakakibara:
Grammatical Inference: Algorithms and Applications, 7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004, Proceedings. Lecture Notes in Computer Science 3264, Springer 2004, ISBN 3-540-23410-1 [contents] - 2003
- [j12]Yasubumi Sakakibara:
DNA-based algorithms for learning Boolean formulae. Nat. Comput. 2(2): 153-171 (2003) - [c24]Yasubumi Sakakibara, Takahiro Hohsaka:
In Vitro Translation-Based Computations. DNA 2003: 197-202 - [c23]Yasubumi Sakakibara:
Pair hidden Markov models on tree structures. ISMB (Supplement of Bioinformatics) 2003: 232-240 - 2002
- [c22]Takashi Yokomori, Yasubumi Sakakibara, Satoshi Kobayashi:
A Magic Pot : Self-assembly Computation Revisited. Formal and Natural Computing 2002: 418-430 - [c21]Yasubumi Sakakibara, Hiroshi Imai:
A DNA-based Computational Model Using a Specific Type of Restriction Enzyme. DNA 2002: 315-325 - 2001
- [j11]Yasubumi Sakakibara, Satoshi Kobayashi:
Sticker systems with complex structures. Soft Comput. 5(2): 114-120 (2001) - [j10]Satoshi Kobayashi, Yasubumi Sakakibara:
Multiple splicing systems and the universal computability. Theor. Comput. Sci. 264(1): 3-23 (2001) - [c20]Satoshi Kobayashi, Yasubumi Sakakibara, Takashi Yokomori:
Approximate identification of finite elasticity. Where Mathematics, Computer Science, Linguistics and Biology Meet 2001: 277-286 - [c19]Yasubumi Sakakibara:
Probabilistic logical inference using quantities of DNA strands. CEC 2001: 797-804 - [c18]Yasubumi Sakakibara:
Population Computation and Majority Inference in Test Tube. DNA 2001: 82-91 - 2000
- [c17]Yasubumi Sakakibara:
Solving Computational Learning Problems of Boolean Formulae on DNA Computers. DNA Computing 2000: 220-230 - [c16]Yasubumi Sakakibara, Hidenori Muramatsu:
Learning Context-Free Grammars from Partially Structured Examples. ICGI 2000: 229-240
1990 – 1999
- 1999
- [j9]Yasubumi Sakakibara, Claudio Ferretti:
Splicing on Tree-Like Structures. Theor. Comput. Sci. 210(2): 227-243 (1999) - [c15]Yasubumi Sakakibara, Mitsuhiro Kondo:
GA-based Learning of Context-Free Grammars using Tabular Representations. ICML 1999: 354-360 - 1997
- [j8]Christoph Globig, Klaus P. Jantke, Steffen Lange, Yasubumi Sakakibara:
On Case Based Learnability of Language. New Gener. Comput. 15(1): 39-83 (1997) - [j7]Yasubumi Sakakibara:
Recent Advances of Grammatical Inference. Theor. Comput. Sci. 185(1): 15-45 (1997) - [c14]Yasubumi Sakakibara, Claudio Ferretti:
Splicing on tree-like structures. DNA Based Computers 1997: 361-375 - 1996
- [j6]Yasubumi Sakakibara, Kazuo Misue, Takeshi Koshiba:
A machine learning approach to knowledge acquisitions from text databases. Int. J. Hum. Comput. Interact. 8(3): 309-324 (1996) - [c13]Mostefa Golea, Masahiro Matsuoka, Yasubumi Sakakibara:
Stochastic simple recurrent neural networks. ICGI 1996: 262-273 - 1995
- [c12]Yasubumi Sakakibara:
Grammatical Inference: An Old and New Paradigm. ALT 1995: 1-24 - [c11]Yasubumi Sakakibara, Mostefa Golea:
Simple recurrent networks as generalized hidden Markov models with distributed representations. ICNN 1995: 979-984 - 1994
- [c10]Yasubumi Sakakibara, Klaus P. Jantke, Steffen Lange:
Learning Languages by Collecting Cases and Tuning Parameters. AII/ALT 1994: 532-546 - [c9]Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood, David Haussler:
Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars. CPM 1994: 289-306 - [c8]Yasubumi Sakakibara, Michael Brown, Rebecca C. Underwood, I. Saira Mian, David Haussler:
Stochastic Context-Free Grammars for Modeling RN. HICSS (5) 1994: 284-294 - 1993
- [j5]Yasubumi Sakakibara:
Noise-Tolerant Occam Algorithms and Their Applications to Learning Decision Trees. Mach. Learn. 11: 37-62 (1993) - 1992
- [j4]Yasubumi Sakakibara:
Efficient Learning of Context-Free Grammars from Positive Structural Examples. Inf. Comput. 97(1): 23-60 (1992) - [c7]Yasubumi Sakakibara, Rani Siromoney:
A Noise Model on Learning Sets of Strings. COLT 1992: 295-302 - 1991
- [j3]Yasubumi Sakakibara:
On Learning from Queries and Counterexamples in the Presence of Noise. Inf. Process. Lett. 37(5): 279-284 (1991) - [c6]Yuji Takada, Yasubumi Sakakibara, Takeshi Ohtani:
ACE: A syntax-directed editor customizable from examples and queries. ALT 1991: 126-138 - 1990
- [j2]Yasubumi Sakakibara:
Inductive inference of logic programs based on algebraic semantics. New Gener. Comput. 7(4): 365-380 (1990) - [j1]Yasubumi Sakakibara:
Learning Context-Free Grammars from Structural Data in Polynomial Time. Theor. Comput. Sci. 76(2-3): 223-242 (1990) - [c5]Yasubumi Sakakibara:
Occam Algorithms for Learning From Noisy Examples. ALT 1990: 193-208 - [c4]Yuji Takada, Kunihiko Hiraishi, Yasubumi Sakakibara:
Exact Learning of Semilinear Sets. ALT 1990: 314-324
1980 – 1989
- 1988
- [c3]Yasubumi Sakakibara:
Learning Context-Free Grammars from Structural Data in Polynomial Time. COLT 1988: 330-344 - [c2]Yasubumi Sakakibara:
An Efficient Learning of Context-Free Grammars for Bottom-Up Parsers. FGCS 1988: 447-454 - 1986
- [c1]Yasubumi Sakakibara:
Programming in Modal Logic: An Extension of PROLOG based on Modal Logic. LP 1986: 81-91
Coauthor Index
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