Hiroshi Mamitsuka

	2012
68		David duVerle, Hiroshi Mamitsuka: A review of statistical methods for prediction of proteolytic cleavage. Briefings in Bioinformatics 13(3): 337-349 (2012)
67		Lianming Zhang, Keiko Udaka, Hiroshi Mamitsuka, Shanfeng Zhu: Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools. Briefings in Bioinformatics 13(3): 350-364 (2012)
66		Motoki Shiga, Hiroshi Mamitsuka: A Variational Bayesian Framework for Clustering with Multiple Graphs. IEEE Trans. Knowl. Data Eng. 24(4): 577-590 (2012)
65		Motoki Shiga, Hiroshi Mamitsuka: Efficient semi-supervised learning on locally informative multiple graphs. Pattern Recognition 45(3): 1035-1049 (2012)
	2011
64		Canh Hao Nguyen, Hiroshi Mamitsuka: Kernels for Link Prediction with Latent Feature Models. ECML/PKDD (2) 2011: 517-532
63		Canh Hao Nguyen, Hiroshi Mamitsuka: Discriminative Graph Embedding for Label Propagation. IEEE Transactions on Neural Networks 22(9): 1395-1405 (2011)
62		Ichigaku Takigawa, Hiroshi Mamitsuka: Efficiently mining δ-tolerance closed frequent subgraphs. Machine Learning 82(2): 95-121 (2011)
61		Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka: A spectral approach to clustering numerical vectors as nodes in a network. Pattern Recognition 44(2): 236-251 (2011)
60		Motoki Shiga, Hiroshi Mamitsuka: Clustering genes with expression and beyond. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 1(6): 496-511 (2011)
	2010
59		Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Hiroshi Mamitsuka, Mineichi Kudo: Algorithms for Finding a Minimum Repetition Representation of a String. SPIRE 2010: 185-190
58		Timothy Hancock, Ichigaku Takigawa, Hiroshi Mamitsuka: Mining metabolic pathways through gene expression. Bioinformatics 26(17): 2128-2135 (2010)
57		Timothy Hancock, Hiroshi Mamitsuka: Boosted Optimization for Network Classification. Journal of Machine Learning Research - Proceedings Track 9: 305-312 (2010)
56		Xihao Hu, Wenjian Zhou, Keiko Udaka, Hiroshi Mamitsuka, Shanfeng Zhu: MetaMHC: a meta approach to predict peptides binding to MHC molecules. Nucleic Acids Research 38(Web-Server-Issue): 474-479 (2010)
	2009
55		Raymond Wan, Vo Ngoc Anh, Hiroshi Mamitsuka: Efficient Probabilistic Latent Semantic Analysis through Parallelization. AIRS 2009: 432-443
54		Timothy Hancock, Hiroshi Mamitsuka: A Markov Classification Model for Metabolic Pathways. WABI 2009: 121-132
53		Shanfeng Zhu, Jia Zeng, Hiroshi Mamitsuka: Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity. Bioinformatics 25(15): 1944-1951 (2009)
52		Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka: Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. Bioinformatics 25(21): 2735-2743 (2009)
51		Shanfeng Zhu, Ichigaku Takigawa, Jia Zeng, Hiroshi Mamitsuka: Field independent probabilistic model for clustering multi-field documents. Inf. Process. Manage. 45(5): 555-570 (2009)
	2008
50		Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka: Mining significant tree patterns in carbohydrate sugar chains. ECCB 2008: 167-173
49		Ichigaku Takigawa, Hiroshi Mamitsuka: Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis. Bioinformatics 24(2): 250-257 (2008)
48		Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka: A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology. TKDD 2(1): (2008)
	2007
47		Shanfeng Zhu, Ichigaku Takigawa, Shuqin Zhang, Hiroshi Mamitsuka: A Probabilistic Model for Clustering Text Documents with Multiple Fields. ECIR 2007: 331-342
46		Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka: Annotating gene function by combining expression data with a modular gene network. ISMB/ECCB (Supplement of Bioinformatics) 2007: 468-478
45		Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka: A spectral clustering approach to optimally combining numericalvectors with a modular network. KDD 2007: 647-656
44		Raymond Wan, Vo Ngoc Anh, Hiroshi Mamitsuka: Passage Retrieval with Vector Space and Query-Level Aspect Models. TREC 2007
43		Takashi Yoneya, Hiroshi Mamitsuka: A hidden Markov model-based approach for identifying timing differences in gene expression under different experimental factors. Bioinformatics 23(7): 842-849 (2007)
42		Hiroshi Mamitsuka, Naoki Abe: Active ensemble learning: Application to data mining and bioinformatics. Systems and Computers in Japan 38(11): 100-108 (2007)
	2006
41		Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Hiroshi Mamitsuka, Minoru Kanehisa: ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains. ISMB (Supplement of Bioinformatics) 2006: 25-34
40		Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka: A new efficient probabilistic model for mining labeled ordered trees. KDD 2006: 177-186
39		Raymond Wan, Ichigaku Takigawa, Hiroshi Mamitsuka, Vo Ngoc Anh: Combining Vector-Space and Word-Based Aspect Models for Passage Retrieval. TREC 2006
38		Raymond Wan, Ichigaku Takigawa, Hiroshi Mamitsuka: Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data. VDMB 2006: 40-49
37		Shanfeng Zhu, Keiko Udaka, John Sidney, Alessandro Sette, Kiyoko F. Aoki-Kinoshita, Hiroshi Mamitsuka: Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules. Bioinformatics 22(13): 1648-1655 (2006)
36		Hiroshi Mamitsuka: Query-learning-based iterative feature-subset selection for learning from high-dimensional data sets. Knowl. Inf. Syst. 9(1): 91-108 (2006)
35		Hiroshi Mamitsuka: Selecting features in microarray classification using ROC curves. Pattern Recognition 39(12): 2393-2404 (2006)
	2005
34		Shanfeng Zhu, Yasushi Okuno, Gozoh Tsujimoto, Hiroshi Mamitsuka: A probabilistic model for mining implicit 'chemical compound-gene' relations from literature. ECCB/JBI 2005: 251
33		Raymond Wan, Hiroshi Mamitsuka, Kiyoko F. Aoki: Cleaning microarray expression data using Markov random fields based on profile similarity. SAC 2005: 206-207
32		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)
31		Hiroshi Mamitsuka: Finding the biologically optimal alignment of multiple sequences. Artificial Intelligence in Medicine 35(1-2): 9-18 (2005)
30		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)
29		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)
28		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)
	2004
27		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
26		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
25		Nobuhisa Ueda, Kiyoko F. Aoki, Hiroshi Mamitsuka: A General Probabilistic Framework for Mining Labeled Ordered Trees. SDM 2004
24		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)
23		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)
22		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)
	2003
21		Hiroshi Mamitsuka: Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a High-Dimensional Database in Drug Desig. BIBE 2003: 253-257
20		Hiroshi Mamitsuka: Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based Clustering. BIBE 2003: 385-392
19		Hiroshi Mamitsuka: Efficient Mining from Heterogeneous Data Sets for Predicting Protein-Protein Interactions. DEXA Workshops 2003: 32-36
18		Hiroshi Mamitsuka: Hierarchical Latent Knowledge Analysis for Co-occurrence Data. ICML 2003: 504-511
17		Hiroshi Mamitsuka: Selective Sampling with a Hierarchical Latent Variable Model. IDA 2003: 352-363
16		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
15		Hiroshi Mamitsuka: Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data. SDM 2003
14		Hiroshi Mamitsuka, Yasushi Okuno, Atsuko Yamaguchi: Mining biologically active patterns in metabolic pathways using microarray expression profiles. SIGKDD Explorations 5(2): 113-121 (2003)
	2002
13		Hiroshi Mamitsuka: Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases. PKDD 2002: 361-372
12		Hiroshi Mamitsuka, Naoki Abe: Efficient Data Mining by Active Learning. Progress in Discovery Science 2002: 258-267
	2000
11		Hiroshi Mamitsuka, Naoki Abe: Efficient Mining from Large Databases by Query Learning. ICML 2000: 575-582
	1998
10		Naoki Abe, Hiroshi Mamitsuka, Atsuyoshi Nakamura: Empirical Comparison of Competing Query Learning Methods. Discovery Science 1998: 387-388
9		Naoki Abe, Hiroshi Mamitsuka: Query Learning Strategies Using Boosting and Bagging. ICML 1998: 1-9
	1997
8		Hiroshi Mamitsuka: Supervised learning of hidden Markov models for sequence discrimination. RECOMB 1997: 202-208
7		Naoki Abe, Hiroshi Mamitsuka: Predicting Protein Secondary Structure Using Stochastic Tree Grammars. Machine Learning 29(2-3): 275-301 (1997)
	1996
6		Hiroshi Mamitsuka: A Learning Method of Hidden Markov Models for Sequence Discrimination. Journal of Computational Biology 3(3): 361-374 (1996)
	1995
5		Hiroshi Mamitsuka, Kenji Yamanishi: alpha-Helix region prediction with stochastic rule learning. Computer Applications in the Biosciences 11(4): 399-411 (1995)
4		Hiroshi Mamitsuka: Representing inter-residue dependencies in protein sequences with probabilistic networks. Computer Applications in the Biosciences 11(4): 413-422 (1995)
	1994
3		Naoki Abe, Hiroshi Mamitsuka: A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars. ICML 1994: 3-11
2		Hiroshi Mamitsuka, Naoki Abe: Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars. ISMB 1994: 276-284
	1992
1		Hiroshi Mamitsuka, Kenji Yamanishi: Protein Secondary Structure Prediction Based on Stochastic-Rule Learning. ALT 1992: 240-251

Coauthor Index

1	Naoki Abe	[2] [3] [7] [9] [10] [11] [12] [42]
2	Tatsuya Akutsu	[22] [23] [26] [29] [30]
3	Vo Ngoc Anh	[39] [44] [55]
4	Kiyoko F. Aoki-Kinoshita (Kiyoko F. Aoki)	[22] [23] [24] [25] [26] [29] [30] [33] [37] [40] [41] [48]
5	Krzysztof J. Cios	[32]
6	Susumu Goto	[23]
7	Timothy Hancock	[54] [57] [58]
8	Kosuke Hashimoto	[40] [48] [50]
9	Xihao Hu	[56]
10	Minoru Kanehisa	[22] [23] [26] [30] [40] [41] [48] [50]
11	Mitsunori Kayano	[52]
12	Mineichi Kudo	[59]
13	Tomomasa Nagashima	[32]
14	Atsuyoshi Nakamura	[10] [59]
15	Canh Hao Nguyen	[63] [64]
16	Yasushi Okuno	[14] [27] [34]
17	Tomoya Saito	[59]
18	Alessandro Sette	[37]
19	Motoki Shiga	[45] [46] [50] [52] [60] [61] [65] [66]
20	John Sidney	[37]
21	Ryszard Tadeusiewicz	[32]
22	Ichigaku Takigawa	[38] [39] [45] [46] [47] [49] [50] [51] [52] [58] [59] [61] [62]
23	Koji Tsuda	[52]
24	Gozoh Tsujimoto	[34]
25	Keiko Udaka	[37] [56] [67]
26	Nobuhisa Ueda	[22] [23] [25] [26] [29] [40] [41] [48]
27	Raymond Wan	[33] [38] [39] [44] [55]
28	Atsuko Yamaguchi	[14] [16] [22] [23] [24] [26] [29]
29	Kenji Yamanishi	[1] [5]
30	Takashi Yoneya	[43]
31	Jia Zeng	[51] [53]
32	Lianming Zhang	[67]
33	Shuqin Zhang	[47]
34	Wenjian Zhou	[56]
35	Shanfeng Zhu	[34] [37] [47] [51] [53] [56] [67]
36	David duVerle	[68]

Colors in the list of coauthors

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