Hiroshi Mamitsuka Papers on DiSC'06 A probabilistic model for mining labeled ordered trees: capturing patterns in carbohydrate sugar chains Publications Note: Links lead to the DBLP on the Web. Hiroshi Mamitsuka Hiroshi Mamitsuka: Query-learning-based iterative feature-subset selection for learning from high-dimensional data sets. Knowl. Inf. Syst. 9 (1): 91-108 (2006) Raymond Wan , Hiroshi Mamitsuka, Kiyoko F. Aoki : Cleaning microarray expression data using Markov random fields based on profile similarity. SAC 2005 : 206-207 Krzysztof J. Cios , Hiroshi Mamitsuka, Tomomasa Nagashima , Ryszard Tadeusiewicz : Computational intelligence in solving bioinformatics problems. Artificial Intelligence in Medicine 35 (1-2): 1-8 (2005) Hiroshi Mamitsuka: Finding the biologically optimal alignment of multiple sequences. Artificial Intelligence in Medicine 35 (1-2): 9-18 (2005) Kiyoko F. Aoki , Hiroshi Mamitsuka, Tatsuya Akutsu , Minoru Kanehisa : A score matrix to reveal the hidden links in glycans. Bioinformatics 21 (8): 1457-1463 (2005) Nobuhisa Ueda , Kiyoko F. Aoki-Kinoshita , Atsuko Yamaguchi , Tatsuya Akutsu , Hiroshi Mamitsuka: A Probabilistic Model for Mining Labeled Ordered Trees: Capturing Patterns in Carbohydrate Sugar Chains. IEEE Trans. Knowl. Data Eng. 17 (8): 1051-1064 (2005) Hiroshi Mamitsuka: Essential Latent Knowledge for Protein-Protein Interactions: Analysis by an Unsupervised Learning Approach. IEEE/ACM Trans. Comput. Biology Bioinform. 2 (2): 119-130 (2005) Hiroshi Mamitsuka, Yasushi Okuno : A Hierarchical Mixture of Markov Models for Finding Biologically Active Metabolic Paths Using Gene Expression and Protein Classes. CSB 2004 : 341-352 Kiyoko F. Aoki , Nobuhisa Ueda , Atsuko Yamaguchi , Minoru Kanehisa , Tatsuya Akutsu , Hiroshi Mamitsuka: Application of a new probabilistic model for recognizing complex patterns in glycans. ISMB/ECCB (Supplement of Bioinformatics) 2004 : 6-14 Nobuhisa Ueda , Kiyoko Aoki , Hiroshi Mamitsuka: A General Probabilistic Framework for Mining Labeled Ordered Trees. SDM 2004 Atsuko Yamaguchi , Kiyoko F. Aoki , Hiroshi Mamitsuka: Finding the maximum common subgraph of a partial k -tree and a graph with a polynomially bounded number of spanning trees. Inf. Process. Lett. 92 (2): 57-63 (2004) Kiyoko F. Aoki , Atsuko Yamaguchi , Nobuhisa Ueda , Tatsuya Akutsu , Hiroshi Mamitsuka, Susumu Goto , Minoru Kanehisa : KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains. Nucleic Acids Research 32 (Web-Server-Issue): 267-272 (2004) Kiyoko F. Aoki , Nobuhisa Ueda , Atsuko Yamaguchi , Tatsuya Akutsu , Minoru Kanehisa , Hiroshi Mamitsuka: Managing and Analyzing Carbohydrate Data. SIGMOD Record 33 (2): 33-38 (2004) Hiroshi Mamitsuka: Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a High-Dimensional Database in Drug Desig. BIBE 2003 : 253-257 Hiroshi Mamitsuka: Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based Clustering. BIBE 2003 : 385-392 Hiroshi Mamitsuka: Efficient Mining from Heterogeneous Data Sets for Predicting Protein-Protein Interactions. DEXA Workshops 2003 : 32-36 Hiroshi Mamitsuka: Hierarchical Latent Knowledge Analysis for Co-occurrence Data. ICML 2003 : 504-511 Hiroshi Mamitsuka: Selective Sampling with a Hierarchical Latent Variable Model. IDA 2003 : 352-363 Atsuko Yamaguchi , Hiroshi Mamitsuka: Finding the Maximum Common Subgraph of a Partial k-Tree and a Graph with a Polynomially Bounded Number of Spanning Trees. ISAAC 2003 : 58-67 Hiroshi Mamitsuka: Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data. SDM 2003 Hiroshi Mamitsuka, Yasushi Okuno , Atsuko Yamaguchi : Mining biologically active patterns in metabolic pathways using microarray expression profiles. SIGKDD Explorations 5 (2): 113-121 (2003) Hiroshi Mamitsuka: Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases. PKDD 2002 : 361-372 Hiroshi Mamitsuka, Naoki Abe : Efficient Data Mining by Active Learning. Progress in Discovery Science 2002 : 258-267 Hiroshi Mamitsuka, Naoki Abe : Efficient Mining from Large Databases by Query Learning. ICML 2000 : 575-582 Naoki Abe , Hiroshi Mamitsuka, Atsuyoshi Nakamura : Empirical Comparison of Competing Query Learning Methods. Discovery Science 1998 : 387-388 Naoki Abe , Hiroshi Mamitsuka: Query Learning Strategies Using Boosting and Bagging. ICML 1998 : 1-9 Hiroshi Mamitsuka: Supervised learning of hidden Markov models for sequence discrimination. RECOMB 1997 : 202-208 Naoki Abe , Hiroshi Mamitsuka: Predicting Protein Secondary Structure Using Stochastic Tree Grammars. Machine Learning 29 (2-3): 275-301 (1997) Hiroshi Mamitsuka: A Learning Method of Hidden Markov Models for Sequence Discrimination. Journal of Computational Biology 3 (3): 361-374 (1996) Hiroshi Mamitsuka, Kenji Yamanishi : alpha-Helix region prediction with stochastic rule learning. Computer Applications in the Biosciences 11 (4): 399-411 (1995) Hiroshi Mamitsuka: Representing inter-residue dependencies in protein sequences with probabilistic networks. Computer Applications in the Biosciences 11 (4): 413-422 (1995) Naoki Abe , Hiroshi Mamitsuka: A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars. ICML 1994 : 3-11 Hiroshi Mamitsuka, Naoki Abe : Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars. ISMB 1994 : 276-284 Hiroshi Mamitsuka, Kenji Yamanishi : Protein Secondary Structure Prediction Based on Stochastic-Rule Learning. ALT 1992 : 240-251 1 [ 2 ] [ 3 ] [ 7 ] [ 9 ] [ 10 ] [ 11 ] [ 12 ] 2 [ 22 ] [ 23 ] [ 26 ] [ 29 ] [ 30 ] 3 [ 25 ] 4 [ 22 ] [ 23 ] [ 24 ] [ 26 ] [ 30 ] [ 33 ] 5 [ 29 ] 6 [ 32 ] 7 [ 23 ] 8 [ 22 ] [ 23 ] [ 26 ] [ 30 ] 9 [ 32 ] 10 [ 10 ] 11 [ 14 ] [ 27 ] 12 [ 32 ] 13 [ 22 ] [ 23 ] [ 25 ] [ 26 ] [ 29 ] 14 [ 33 ] 15 [ 14 ] [ 16 ] [ 22 ] [ 23 ] [ 24 ] [ 26 ] [ 29 ] 16 [ 1 ] [ 5 ] ©2006 Association for Computing Machinery