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746 results on '"Maruyama, Osamu"'

13. Two Challenging Difficulties of Protein Complex Prediction

Author

Maruyama, Osamu, Wakayama, Masato, Editor-in-Chief, Anderssen, Robert S., Series Editor, Bauschke, Heinz H., Series Editor, Broadbridge, Philip, Series Editor, Cheng, Jin, Series Editor, Chyba, Monique, Series Editor, Cottet, Georges-Henri, Series Editor, Cuminato, José Alberto, Series Editor, Ei, Shin-ichiro, Series Editor, Fukumoto, Yasuhide, Series Editor, Hosking, Jonathan R. M., Series Editor, Jofré, Alejandro, Series Editor, Landman, Kerry, Series Editor, McKibbin, Robert, Series Editor, Parmeggiani, Andrea, Series Editor, Pipher, Jill, Series Editor, Polthier, Konrad, Series Editor, Saeki, Osamu, Series Editor, Schilders, Wil, Series Editor, Shen, Zuowei, Series Editor, Toh, Kim Chuan, Series Editor, Verbitskiy, Evgeny, Series Editor, Yoshida, Nakahiro, Series Editor, Kajiwara, Kenji, editor, Simpson, Matthew, editor, and Turner, Ian, editor

Published
2018
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17. Supplementary Figure 4 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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18. Supplementary Table 5 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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19. Supplementary Figure 2B from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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20. Supplementary Table 2 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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21. Supplementary Table 3 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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22. Supplementary Table 4 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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23. Supplementary Table 1 from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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24. Supplementary Figure 1A from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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25. Supplementary Figure 3A-C from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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26. Five Supplementary Tables from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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27. Four Supplementary Figures from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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28. Legends to Supplementary Figures from Hypoxia-Inducible Protein 2 (HIG2), a Novel Diagnostic Marker for Renal Cell Carcinoma and Potential Target for Molecular Therapy

Author

Togashi, Akira, primary, Katagiri, Toyomasa, primary, Ashida, Shingo, primary, Fujioka, Tomoaki, primary, Maruyama, Osamu, primary, Wakumoto, Yoshiaki, primary, Sakamoto, Yoshiro, primary, Fujime, Makoto, primary, Kawachi, Yoshio, primary, Shuin, Taro, primary, and Nakamura, Yusuke, primary

Published
2023
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30. Markov Chain Monte Carlo Algorithms

Author

Maruyama, Osamu, Wakayama, Masato, Editor-in-chief, Anderssen, Robert S., Series editor, Bauschke, Heinz H., Series editor, Broadbridge, Philip, Series editor, Cheng, Jin, Series editor, Chyba, Monique, Series editor, Cottet, Georges-Henri, Series editor, Cuminato, José Alberto, Series editor, Ei, Shin-ichiro, Series editor, Fukumoto, Yasuhide, Series editor, Hosking, Jonathan R. M., Series editor, Jofré, Alejandro, Series editor, Landman, Kerry, Series editor, McKibbin, Robert, Series editor, Mercer, Geoff, Series editor, Parmeggiani, Andrea, Series editor, Pipher, Jill, Series editor, Polthier, Konrad, Series editor, Schilders, Wil, Series editor, Shen, Zuowei, Series editor, Toh, Kim-Chuan, Series editor, Verbitskiy, Evgeny, Series editor, Yoshida, Nakahiro, Series editor, Nishii, Ryuei, editor, Koiso, Miyuki, editor, Ochiai, Hiroyuki, editor, Okada, Kanzo, editor, Saito, Shingo, editor, and Shirai, Tomoyuki, editor

Published
2014
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38. Reconstructing Phylogenetic Trees of Prokaryote Genomes by Randomly Sampling Oligopeptides

Author

Maruyama, Osamu, Matsuda, Akiko, Kuhara, Satoru, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sunderam, Vaidy S., editor, van Albada, Geert Dick, editor, Sloot, Peter M. A., editor, and Dongarra, Jack J., editor

Published
2005
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40. Innovative experimental animal models for real‐time comparison of antithrombogenicity between two oxygenators using dual extracorporeal circulation circuits and indocyanine green fluorescence imaging

Author

Sakurai, Hironobu, primary, Fujiwara, Tatsuki, additional, Ohuchi, Katsuhiro, additional, Hijikata, Wataru, additional, Inoue, Yusuke, additional, Maruyama, Osamu, additional, Tahara, Tomoki, additional, Yokota, Sachie, additional, Tanaka, Yui, additional, Takewa, Yoshiaki, additional, Mizuno, Tomohiro, additional, and Arai, Hirokuni, additional

Published
2022
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41. Searching for Regulatory Elements of Alternative Splicing Events Using Phylogenetic Footprinting

Author

Shigemizu, Daichi, Maruyama, Osamu, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael, editor, Jonassen, Inge, editor, and Kim, Junhyong, editor

Published
2004
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45. Learning Conformation Rules

Author

Maruyama, Osamu, Shoudai, Takayoshi, Furuichi, Emiko, Kuhara, Satoru, Miyano, Satoru, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Jantke, Klaus P., editor, and Shinohara, Ayumi, editor

Published
2001
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48. Additional file 1 of CMIC: predicting DNA methylation inheritance of CpG islands with embedding vectors of variable-length k-mers

Author

Maruyama, Osamu, Li, Yinuo, Narita, Hiroki, Toh, Hidehiro, Au Yeung, Wan Kin, and Sasaki, Hiroyuki

Abstract

Additional file 1. Fig. S1. Distribution of methylation ratios in the maternal genome of mouse blastocyst of the CGIs that are methylated in FGOs. The lower bound of class M (methylated) for FGOs is set to βM = 0.8 as shown in Table. 2. Fig. S2. Balanced accuracy of CMIC with different pairs of kmin and kmax. The search space of the pairs of kmin and kmax are set to be kmin = 2, . . . , 11 and kmax = 3, . . . , 12 with kmax − kmin ≥ 1. The bars are grouped by kmax. Fig. S3. MCC of CMIC with different pairs of kmin and kmax. The search space of the pairs of kmin and kmax are set to be kmin = 2, ..., 11 and kmax = 3, ..., 12 with kmax − kmin ≥ 1. The bars are grouped by kmax. Fig. S4. AUC of CMIC with different pairs of kmin and kmax. The search space of the pairs of kmin and kmax are set to be kmin = 2, ..., 11 and kmax = 3, ..., 12 with kmax − kmin ≥ 1. The bars are grouped by kmax. Fig. S5. Balanced accuracy with different schemes for embedding vectors shown in Table 3. The x-axis represents the eight methods to be compared: splitDNA2vec-C, splitDNA2vec-V, splitDNA2vec-sh-C, splitDNA2vec-sh-V, dna2vec-C, dna2vec-V, dna2vec-N1000-C, and dna2vec-N1000-V. The y-axis shows the F-measure on test datasets. Fig. S6. MCC with different schemes for embedding vectors shown in Table 3. The x-axis represents the eight methods to be compared: splitDNA2vec-C, splitDNA2vec-V, splitDNA2vec-sh-C, splitDNA2vec-sh-V, dna2vec-C, dna2vec-V, dna2vec-N1000-C, and dna2vec-N1000-V. The y-axis shows the F-measure on test datasets. Fig. S7. AUC with different schemes for embedding vectors shown in Table 3. The x-axis represents the eight methods to be compared: splitDNA2vec-C, splitDNA2vec-V, splitDNA2vec-sh-C, splitDNA2vec-sh-V, dna2vec-C, dna2vec-V, dna2vec-N1000-C, and dna2vec-N1000-V. The y-axis shows the F-measure on test datasets. Fig. S8. Balanced accuracy of CMIC with different numbers of variable-length k-mer sequences generated from an input CGI sequence, N. The x-axis represents values of N. The y-axis shows the F-measure with N. Fig. S9. MCC of CMIC with different numbers of variable-length k-mer sequences generated from an input CGI sequence, N. The x-axis represents values of N. The y-axis shows the F-measure with N. Fig. S10. AUC of CMIC with different numbers of variable-length k-mer sequences generated from an input CGI sequence, N. The x-axis represents values of N. The y-axis shows the F-measure with N. Fig. S11. Balanced accuracy of CMIC trained with short CGIs for long CGIs. The x-axis indicates the range of CGI sequence lengths. The y-axis indicates the F-measure. Fig. S12. MCC of CMIC trained with short CGIs for long CGIs. The x-axis indicates the range of CGI sequence lengths. The y-axis indicates the F-measure. Fig. S13. AUC of CMIC trained with short CGIs for long CGIs. The x-axis indicates the range of CGI sequence lengths. The y-axis indicates the F-measure. Fig. S14. Balanced accuracy of CMIC with alternative recurrent units, RNN, BiRNN, GRU, BiGRU, LSTM, and BiLSTM. Fig. S15. MCC of CMIC with alternative recurrent units, RNN, BiRNN, GRU, BiGRU, LSTM, and BiLSTM. Fig. S16. AUC of CMIC with alternative recurrent units, RNN, BiRNN, GRU, BiGRU, LSTM, and BiLSTM. Fig. S17. Balanced accuracy of KEGRU with various lengths of k-mers and strides. The vector size is set to 20. The x-axis represents a pair of k and stride. Fig. S18. MCC of KEGRU with various lengths of k-mers and strides. The vector size is set to 20. The x-axis represents a pair of k and stride. Fig. S19. AUC of KEGRU with various lengths of k-mers and strides. The vector size is set to 20. The x-axis represents a pair of k and stride. Fig. S20. Balanced accuracy of KEGRU with various lengths of k-mers and strides. The vector size is set to 50. The x-axis represents a pair of k and stride. Fig. S21. MCC of KEGRU with various lengths of k-mers and strides. The vector size is set to 50. The x-axis represents a pair of k and stride. Fig. S22. AUC of KEGRU with various lengths of k-mers and strides. The vector size is set to 50. The x-axis represents a pair of k and stride. Fig. S23. Plot generated by t-SNE with perplexity 10. Fig. S24. Plot generated by t-SNE with perplexity 50.

Published
2022
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