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Research Output 1987 2019

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Conference contribution
2012

Poster: In silico microarray algorithm: Accurate and fast taxonomic profiling from short read sequences

Tagami, T., Hachiya, T. & Sakakibara, Y., 2012, 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012. 6182660

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Microarrays
Profiling
Microarray
Chemical analysis
High Accuracy
2011
13 Citations (Scopus)

MetaVelvet: AAAn extension of Velvet assembler to de novo metagenome assembly from short sequence reads

Namiki, T., Hachiya, T., Tanaka, H. & Sakakibara, Y., 2011, 2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2011. p. 116-124 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Metagenome
Genes
Genome
Scaffolds
Metagenomics
2010

Development of a bacteria computer: From in silico finite automata to in vitro and in vivo

Sakakibara, Y., 2010, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6158 LNCS. p. 362-371 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 6158 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Finite Automata
Finite automata
Bacteria
Finite State Automata
Escherichia Coli
3 Citations (Scopus)

Improvement of structure conservation index with centroid estimators

Okada, Y., Sato, K. & Sakakibara, Y., 2010, Pacific Symposium on Biocomputing 2010, PSB 2010. p. 88-97 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Untranslated RNA
Conservation
RNA
Genome
Support vector machines
2009
1 Citation (Scopus)

A non-parametric bayesian approach for predicting RNA secondary structures

Sato, K., Hamada, M., Mituyama, T., Asai, K. & Sakakibara, Y., 2009, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5724 LNBI. p. 286-297 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5724 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

RNA Secondary Structure
RNA
Bayesian Approach
Dirichlet Process
Structure Prediction

Operon structure optimization by random self-assembly

Nakagawa, Y., Yugi, K., Tsuge, K., Itaya, M., Yanagawa, H. & Sakakibara, Y., 2009, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5347 LNCS. p. 33-40 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5347 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Structure Optimization
Self-assembly
Self assembly
Genes
Gene
2007
1 Citation (Scopus)

Stem kernels for RNA sequence analyses

Sakakibara, Y., Asai, K. & Sato, K., 2007, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4414 LNBI. p. 278-291 14 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

RNA Sequence Analysis
RNA
kernel
Secondary Structure
Genome
2006
11 Citations (Scopus)

Development of an in vivo computer based on Escherichia coli

Nakagawa, H., Sakamoto, K. & Sakakibara, Y., 2006, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3892 LNCS. p. 203-212 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3892 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Escherichia coli
Escherichia Coli
Finite automata
Finite State Automata
Protein Synthesis
1 Citation (Scopus)

Discriminative detection of cis-acting regulatory variation from location data

Kawada, Y. & Sakakibara, Y., 2006, Series on Advances in Bioinformatics and Computational Biology. Vol. 3. p. 89-98 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Genes
Transcription factors
Transcription Factors
Binding sites
Yeast
5 Citations (Scopus)

Intensive in vitro experiments of implementing and executing finite automata in test tube

Kuramochi, J. & Sakakibara, Y., 2006, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3892 LNCS. p. 193-202 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3892 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Finite Automata
Finite automata
Tube
Encoding
Experiment
2005
1 Citation (Scopus)

Discriminative discovery of transcription factor binding sites from location data

Kawada, Y. & Sakakibara, Y., 2005, Proceedings - 2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005. Vol. 2005. p. 86-92 7 p. 1498010

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Transcription factors
Binding sites
Transcription Factors
Genes
Chromatin Immunoprecipitation
2004

Grammatical inference: Algorithms and applications: 7th international colloquium, ICGI 2004 Athens, Greece, october 11-13, 2004 proceedings

Paliouras, G. & Sakakibara, Y., 2004, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Vol. 3264. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3264).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Grammatical Inference
Greece
5 Citations (Scopus)

Pair stochastic tree adjoining grammars for aligning and predicting pseudoknot RNA structures

Matsui, H., Sato, K. & Sakakibara, Y., 2004, Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004. p. 290-299 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

RNA
Context sensitive grammars
Binary codes
Dynamic programming
Websites
2002
1 Citation (Scopus)

Population computation and majority inference in test tube

Sakakibara, Y., 2002, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Vol. 2340. p. 82-91 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 2340).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tube
DNA
Amplification
Inconsistent
Learning Algorithm
2001

Probabilistic logical inference using quantities of DNA strands

Sakakibara, Y., 2001, Proceedings of the IEEE Conference on Evolutionary Computation, ICEC. Vol. 2. p. 797-804 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

DNA
Supervised learning
Gene expression
Computational complexity
Chemical analysis
4 Citations (Scopus)

Solving computational learning problems of boolean formulae on DNA computers

Sakakibara, Y., 2001, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Vol. 2054. p. 220-230 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 2054).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Normal Form
DNA
Term
Computational Learning Theory
Learning
2000
29 Citations (Scopus)

Learning context-free grammars from partially structured examples

Sakakibara, Y. & Muramatsu, H., 2000, Grammatical Inference: Algorithms and Applications - 5th International Colloquium, ICGI 2000, Proceedings. Springer Verlag, Vol. 1891. p. 229-240 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 1891).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Context free grammars
Context-free Grammar
Learning algorithms
Learning Algorithm
Production Rules
1996

Stochastic simple recurrent neural networks

Golea, M., Matsuoka, M. & Sakakibara, Y., 1996, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Vol. 1147. p. 262-273 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 1147).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Recurrent neural networks
Recurrent Neural Networks
Hidden Markov models
Markov Model
Grammatical Inference
1995
2 Citations (Scopus)

Grammatical inference: An old and new paradigm

Sakakibara, Y., 1995, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Vol. 997. p. 1-24 24 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 997).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Grammatical Inference
Context free grammars
Context-free Grammar
Paradigm
Learnability
6 Citations (Scopus)

Simple recurrent networks as generalized hidden Markov models with distributed representations

Sakakibara, Y. & Golea, M., 1995, IEEE International Conference on Neural Networks - Conference Proceedings. IEEE, Vol. 2. p. 979-984 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hidden Markov models
Recurrent neural networks
Dynamic programming
Learning algorithms
32 Citations (Scopus)

Stochastic context-free grammars for modeling RNA

Sakakibara, Y., Brown, M., Underwood, R. C., Mian, I. S. & Haussler, D., 1995, Proceedings of the Hawaii International Conference on System Sciences. Nunamaker, J. F. & Sprague, R. H. J. (eds.). Publ by IEEE, Vol. 5. p. 284-293 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Context free grammars
RNA
Hidden Markov models
DNA
Transfer RNA
1994
4 Citations (Scopus)

Learning languages by collecting cases and tuning parameters

Sakakibara, Y., Jantke, K. P. & Lange, S., 1994, Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings. Springer Verlag, Vol. 872 LNAI. p. 532-546 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 872 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Formal languages
Parameter Tuning
Similarity Measure
Tuning
Context free languages
16 Citations (Scopus)

Recent methods for rna modeling using stochastic context-free grammars

Sakakibara, Y., Brown, M., Hughey, R., Mian, S., Sjölander, K., Underwood, R. C. & Haussler, D., 1994, Combinatorial Pattern Matching - 5th Annual Symposium, CPM 1994, Proceedings. Springer Verlag, Vol. 807 LNCS. p. 290-306 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 807 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Context free grammars
Stochastic Modeling
Context-free Grammar
Tile
Grammar
1993
8 Citations (Scopus)

Text classification and keyword extraction by learning decision trees

Sakakibara, Y., Misue, K. & Koshiba, T., 1993, Proceedings of the Conference on Artificial Intelligence Applications. Publ by IEEE, p. 466 1 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Decision trees
Learning algorithms
Learning systems
Processing
1992
15 Citations (Scopus)

Noise model on learning sets of strings

Sakakibara, Y. & Siromoney, R., 1992, Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory. Publ by ACM, p. 295-302 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Random errors
Learning algorithms
Labels
1987
6 Citations (Scopus)

Programming in modal logic: An extension of PROLOG based on modal logic

Sakakibara, Y., 1987 Jan 1, Logic Programming 1986 - Proceedings of the 5th Conference. Springer Verlag, p. 81-91 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 264 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

PROLOG (programming language)
Logic programming
Modal Logic
Computer programming languages
Programming