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2020 – today
- 2023
[j192]Xiaoti Jia, Pei Zhao, Fuyi Li
, Zhaohui Qin, Haoran Ren, Junzhou Li, Chunbo Miao, Quanzhi Zhao, Tatsuya Akutsu, Gensheng Dou, Zhen Chen, Jiangning Song:
ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning. Briefings Bioinform. 24(2) (2023)- [j191]Jing Xu, Fuyi Li, Chen Li, Xudong Guo, Cornelia Landersdorfer, Hsin-Hui Shen, Anton Y. Peleg, Jian Li, Seiya Imoto, Jianhua Yao, Tatsuya Akutsu, Jiangning Song:
iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities. Briefings Bioinform. 24(4) (2023) - [j190]Tomoya Mori, Toshiro Takase, Kuan-Chun Lan, Junko Yamane, Cantas Alev, Azuma Kimura, Kenji Osafune, Jun K. Yamashita, Tatsuya Akutsu, Hiroaki Kitano, Wataru Fujibuchi:
eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio-temporal architectures of cells. BMC Bioinform. 24(1): 252 (2023) - [j189]Jiazhou Chen, Guoqiang Han, Aodan Xu, Tatsuya Akutsu, Hongmin Cai:
Identifying miRNA-Gene Common and Specific Regulatory Modules for Cancer Subtyping by a High-Order Graph Matching Model. IEEE ACM Trans. Comput. Biol. Bioinform. 20(1): 421-431 (2023) - [j188]Yu Cao, Wenya Pi, Chun-Yu Lin, Ulrike Münzner, Masahiro Ohtomo, Tatsuya Akutsu:
Common Attractors in Multiple Boolean Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 20(5): 2862-2873 (2023) - [j187]Avraham A. Melkman, Sini Guo, Wai-Ki Ching, Pengyu Liu, Tatsuya Akutsu:
On the Compressive Power of Boolean Threshold Autoencoders. IEEE Trans. Neural Networks Learn. Syst. 34(2): 921-931 (2023) - [i15]Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes. CoRR abs/2305.00801 (2023) - 2022
- [j186]Fan Zhang, Jianshen Zhu, Rachaya Chiewvanichakorn, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A new approach to the design of acyclic chemical compounds using skeleton trees and integer linear programming. Appl. Intell. 52(15): 17058-17072 (2022) - [j185]Meng Zhang, Cangzhi Jia, Fuyi Li, Chen Li, Yan Zhu, Tatsuya Akutsu, Geoffrey I. Webb, Quan Zou, Lachlan J. M. Coin, Jiangning Song:
Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction. Briefings Bioinform. 23(2) (2022) - [j184]Chunting Liu, Jiangning Song, Hiroyuki Ogata, Tatsuya Akutsu:
MSNet-4mC: learning effective multi-scale representations for identifying DNA N4-methylcytosine sites. Bioinform. 38(23): 5160-5167 (2022) - [j183]Ruiming Li, Jung-Yu Lee, Jinn-Moon Yang, Tatsuya Akutsu:
Densest subgraph-based methods for protein-protein interaction hot spot prediction. BMC Bioinform. 23(1): 451 (2022) - [j182]Shahid Iqbal, Fang Ge, Fuyi Li, Tatsuya Akutsu, Yuanting Zheng, Robin B. Gasser, Dong-Jun Yu, Geoffrey I. Webb, Jiangning Song:
PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations. J. Chem. Inf. Model. 62(17): 4270-4282 (2022) - [j181]Zhen Chen, Xuhan Liu, Pei Zhao, Chen Li, Yanan Wang, Fuyi Li, Tatsuya Akutsu, Chris Bain, Robin B. Gasser, Junzhou Li, Zuoren Yang, Xin Gao, Lukasz A. Kurgan, Jiangning Song:
iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets. Nucleic Acids Res. 50(W1): 434-447 (2022) - [j180]So Kumano, Tatsuya Akutsu:
Comparison of the Representational Power of Random Forests, Binary Decision Diagrams, and Neural Networks. Neural Comput. 34(4): 1019-1044 (2022) - [j179]Ulrike Münzner, Tomoya Mori, Marcus Krantz, Edda Klipp, Tatsuya Akutsu:
Identification of periodic attractors in Boolean networks using a priori information. PLoS Comput. Biol. 18(1) (2022) - [j178]Trinh Van Giang, Tatsuya Akutsu, Kunihiko Hiraishi:
An FVS-Based Approach to Attractor Detection in Asynchronous Random Boolean Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 806-818 (2022) - [j177]De-Shuang Huang, Kyungsook Han, Tatsuya Akutsu:
Guest Editorial for Special Section on the 16th International Conference on Intelligent Computing (ICIC). IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3124-3125 (2022) - [j176]Jianshen Zhu, Naveed Ahmed Azam, Fan Zhang, Aleksandar Shurbevski, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A Novel Method for Inferring Chemical Compounds With Prescribed Topological Substructures Based on Integer Programming. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3233-3245 (2022) - [j175]Sini Guo, Pengyu Liu, Wai-Ki Ching, Tatsuya Akutsu:
On the Distribution of Successor States in Boolean Threshold Networks. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4147-4159 (2022) - [c95]Jianshen Zhu, Kazuya Haraguchi, Hiroshi Nagamochi, Tatsuya Akutsu:
Adjustive Linear Regression and Its Application to the Inverse QSAR. BIOINFORMATICS 2022: 144-151 - [c94]Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A Method for Molecular Design Based on Linear Regression and Integer Programming. ICBBB 2022: 21-28 - [c93]Tatsuya Akutsu, Tomoya Mori, Naotoshi Nakamura, Satoshi Kozawa, Yuhei Ueno, Thomas N. Sato:
On the Complexity of Tree Edit Distance with Variables. ISAAC 2022: 44:1-44:14 - [i14]Jianshen Zhu, Naveed Ahmed Azam, Shengjuan Cao, Ryota Ido, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
Molecular Design Based on Integer Programming and Quadratic Descriptors in a Two-layered Model. CoRR abs/2209.13527 (2022) - 2021
- [j174]Naveed Ahmed Azam, Jianshen Zhu, Yanming Sun, Yu Shi, Aleksandar Shurbevski, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming. Algorithms Mol. Biol. 16(1): 18 (2021) - [j173]Xiaoqing Cheng, Wai-Ki Ching, Sini Guo, Tatsuya Akutsu:
Discrimination of attractors with noisy nodes in Boolean networks. Autom. 130: 109630 (2021) - [j172]Ruopeng Xie, Jiahui Li, Jiawei Wang, Wei Dai, André Leier, Tatiana T. Marquez-Lago, Tatsuya Akutsu, Trevor Lithgow, Jiangning Song, Yanju Zhang:
DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy. Briefings Bioinform. 22(3) (2021) - [j171]Shutao Mei, Fuyi Li, Dongxu Xiang, Rochelle Ayala, Pouya Faridi, Geoffrey I. Webb, Patricia T. Illing, Jamie Rossjohn, Tatsuya Akutsu, Nathan P. Croft, Anthony W. Purcell, Jiangning Song:
Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules. Briefings Bioinform. 22(5) (2021) - [j170]Shahid Iqbal, Fuyi Li, Tatsuya Akutsu, David B. Ascher, Geoffrey I. Webb, Jiangning Song:
Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations. Briefings Bioinform. 22(6) (2021) - [j169]Pengyu Liu, Jiangning Song, Chun-Yu Lin, Tatsuya Akutsu:
ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites. BMC Bioinform. 22(1): 63 (2021) - [j168]Ruiming Li, Chun-Yu Lin, Weifeng Guo, Tatsuya Akutsu:
Weighted minimum feedback vertex sets and implementation in human cancer genes detection. BMC Bioinform. 22(1): 143 (2021) - [j167]Tatsuya Akutsu, Hongmin Cai:
Editorial: Inference of Biological Networks. Frontiers Bioinform. 1 (2021) - [j166]Motoki Kajiwara, Ritsuki Nomura, Felix Goetze, Masanori Kawabata, Yoshikazu Isomura, Tatsuya Akutsu, Masanori Shimono:
Inhibitory neurons exhibit high controlling ability in the cortical microconnectome. PLoS Comput. Biol. 17(4) (2021) - [j165]Tatsuya Akutsu, Jesper Jansson, Ruiming Li, Atsuhiro Takasu, Takeyuki Tamura:
New and improved algorithms for unordered tree inclusion. Theor. Comput. Sci. 883: 83-98 (2021) - [c92]Naveed Ahmed Azam, Jianshen Zhu, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search. BIBM 2021: 360-363 - [c91]Kouki Tanaka, Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
An Inverse QSAR Method Based on Decision Tree and Integer Programming. ICIC (2) 2021: 628-644 - [c90]Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
An Improved Integer Programming Formulation for Inferring Chemical Compounds with Prescribed Topological Structures. IEA/AIE (1) 2021: 197-209 - [i13]Tatsuya Akutsu, Tomoya Mori, Naotoshi Nakamura, Satoshi Kozawa, Yuhei Ueno, Thomas N. Sato:
Tree Edit Distance with Variables. Measuring the Similarity between Mathematical Formulas. CoRR abs/2105.04802 (2021) - [i12]Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
An Inverse QSAR Method Based on Linear Regression and Integer Programming. CoRR abs/2107.02381 (2021) - [i11]Naveed Ahmed Azam, Jianshen Zhu, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search. CoRR abs/2108.10266 (2021) - [i10]Ryota Ido, Shengjuan Cao, Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A Method for Inferring Polymers Based on Linear Regression and Integer Programming. CoRR abs/2109.02628 (2021) - [i9]Tatsuya Akutsu, Avraham A. Melkman:
On the Size and Width of the Decoder of a Boolean Threshold Autoencoder. CoRR abs/2112.10933 (2021) - 2020
- [j164]Jianshen Zhu, Chenxi Wang, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A Novel Method for Inference of Chemical Compounds of Cycle Index Two with Desired Properties Based on Artificial Neural Networks and Integer Programming. Algorithms 13(5): 124 (2020) - [j163]Zhen Chen, Pei Zhao, Fuyi Li, Tatiana T. Marquez-Lago, André Leier, Jerico Nico De Leon Revote, Yan Zhu, David R. Powell, Tatsuya Akutsu, Geoffrey I. Webb, Kuo-Chen Chou, Alexander Ian Smith, Roger J. Daly, Jian Li, Jiangning Song:
iLearn : an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data. Briefings Bioinform. 21(3): 1047-1057 (2020) - [j162]Shutao Mei, Fuyi Li, André Leier, Tatiana T. Marquez-Lago, Kailin Giam, Nathan P. Croft, Tatsuya Akutsu, Alexander Ian Smith, Jian Li, Jamie Rossjohn, Anthony W. Purcell, Jiangning Song:
A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction. Briefings Bioinform. 21(4): 1119-1135 (2020) - [j161]Weifeng Guo, Shaowu Zhang, Tao Zeng, Tatsuya Akutsu, Luonan Chen:
Network control principles for identifying personalized driver genes in cancer. Briefings Bioinform. 21(5): 1641-1662 (2020) - [j160]Zhen Chen, Pei Zhao, Fuyi Li, Yanan Wang, Alexander Ian Smith, Geoffrey I. Webb, Tatsuya Akutsu, Abdelkader Baggag, Halima Bensmail, Jiangning Song:
Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences. Briefings Bioinform. 21(5): 1676-1696 (2020) - [j159]Yanju Zhang, Sha Yu, Ruopeng Xie, Jiahui Li, André Leier, Tatiana T. Marquez-Lago, Tatsuya Akutsu, Alexander Ian Smith, Zongyuan Ge, Jiawei Wang, Trevor Lithgow, Jiangning Song:
PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins. Bioinform. 36(3): 704-712 (2020) - [j158]Fuyi Li, Jinxiang Chen, André Leier, Tatiana T. Marquez-Lago, Quanzhong Liu, Yanze Wang, Jerico Nico De Leon Revote, Alexander Ian Smith, Tatsuya Akutsu, Geoffrey I. Webb, Lukasz A. Kurgan, Jiangning Song:
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites. Bioinform. 36(4): 1057-1065 (2020) - [j157]Fuyi Li, André Leier, Quanzhong Liu, Yanan Wang, Dongxu Xiang, Tatsuya Akutsu, Geoffrey I. Webb, Alexander Ian Smith, Tatiana T. Marquez-Lago, Jian Li, Jiangning Song:
Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information. Genom. Proteom. Bioinform. 18(1): 52-64 (2020) - [j156]Tatsuya Akutsu, Avraham A. Melkman, Takeyuki Tamura:
Improved Hardness of Maximum Common Subgraph Problems on Labeled Graphs of Bounded Treewidth and Bounded Degree. Int. J. Found. Comput. Sci. 31(2): 253-273 (2020) - [j155]Feiqi Wang, Tatsuya Akutsu, Tomoya Mori:
Comparison of Pseudoknotted RNA Secondary Structures by Topological Centroid Identification and Tree Edit Distance. J. Comput. Biol. 27(9): 1443-1451 (2020) - [j154]Pengyu Liu, Avraham A. Melkman, Tatsuya Akutsu:
Extracting boolean and probabilistic rules from trained neural networks. Neural Networks 126: 300-311 (2020) - [c89]Naveed Ahmed Azam, Rachaya Chiewvanichakorn, Fan Zhang, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A Novel Method for the Inverse QSAR/QSPR based on Artificial Neural Networks and Mixed Integer Linear Programming with Guaranteed Admissibility. BIOINFORMATICS 2020: 101-108 - [c88]Rachaya Chiewvanichakorn, Chenxi Wang, Zhe Zhang, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A Method for the Inverse QSAR/QSPR Based on Artificial Neural Networks and Mixed Integer Linear Programming. ICBBB 2020: 40-46 - [c87]Jingwen Zeng, Hongmin Cai, Tatsuya Akutsu:
Breast Cancer Subtype by Imbalanced Omics Data through A Deep Learning Fusion Model. ICBBB 2020: 78-83 - [c86]Fan Zhang, Jianshen Zhu, Rachaya Chiewvanichakorn, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A New Integer Linear Programming Formulation to the Inverse QSAR/QSPR for Acyclic Chemical Compounds Using Skeleton Trees. IEA/AIE 2020: 433-444 - [i8]Yuui Tamura, Yuhei Nishiyama, Chenxi Wang, Yanming Sun, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
Enumerating Chemical Graphs with Mono-block 2-Augmented Tree Structure from Given Upper and Lower Bounds on Path Frequencies. CoRR abs/2004.06367 (2020) - [i7]Kyousuke Yamashita, Ryuji Masui, Xiang Zhou, Chenxi Wang, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
Enumerating Chemical Graphs with Two Disjoint Cycles Satisfying Given Path Frequency Specifications. CoRR abs/2004.08381 (2020) - [i6]Avraham A. Melkman, Sini Guo, Wai-Ki Ching, Pengyu Liu, Tatsuya Akutsu:
On the Compressive Power of Boolean Threshold Autoencoders. CoRR abs/2004.09735 (2020) - [i5]Naveed Ahmed Azam, Jianshen Zhu, Yanming Sun, Yu Shi, Aleksandar Shurbevski, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A Novel Method for Inference of Acyclic Chemical Compounds with Bounded Branch-height Based on Artificial Neural Networks and Integer Programming. CoRR abs/2009.09646 (2020) - [i4]Xiaoqing Cheng, Wai-Ki Ching, Sini Guo, Tatsuya Akutsu:
Discrimination of attractors with noisy nodes in Boolean networks. CoRR abs/2009.13198 (2020) - [i3]Tatsuya Akutsu, Hiroshi Nagamochi:
A novel method for inference of chemical compounds with prescribed topological substructures based on integer programming. CoRR abs/2010.09203 (2020)
2010 – 2019
- 2019
- [j153]Jiangning Song, Yanan Wang, Fuyi Li, Tatsuya Akutsu, Neil D. Rawlings, Geoffrey I. Webb, Kuo-Chen Chou:
iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites. Briefings Bioinform. 20(2): 638-658 (2019) - [j152]Jiawei Wang, Bingjiao Yang, Yi An, Tatiana T. Marquez-Lago, André Leier, Jonathan Wilksch, Qingyang Hong, Yang Zhang, Morihiro Hayashida, Tatsuya Akutsu, Geoffrey I. Webb, Richard A. Strugnell, Jiangning Song, Trevor Lithgow:
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches. Briefings Bioinform. 20(3): 931-951 (2019) - [j151]Yu Bao, Simone Marini, Takeyuki Tamura, Mayumi Kamada, Shingo Maegawa, Hiroshi Hosokawa, Jiangning Song, Tatsuya Akutsu:
Toward more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features. Briefings Bioinform. 20(5): 1669-1684 (2019) - [j150]Fuyi Li, Yanan Wang, Chen Li, Tatiana T. Marquez-Lago, André Leier, Neil D. Rawlings, Gholamreza Haffari, Jerico Nico De Leon Revote, Tatsuya Akutsu, Kuo-Chen Chou, Anthony W. Purcell, Robert N. Pike, Geoffrey I. Webb, Alexander Ian Smith, Trevor Lithgow, Roger J. Daly, James C. Whisstock, Jiangning Song:
Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods. Briefings Bioinform. 20(6): 2150-2166 (2019) - [j149]Yanju Zhang, Ruopeng Xie, Jiawei Wang, André Leier, Tatiana T. Marquez-Lago, Tatsuya Akutsu, Geoffrey I. Webb, Kuo-Chen Chou, Jiangning Song:
Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework. Briefings Bioinform. 20(6): 2185-2199 (2019) - [j148]Zhen Chen, Xuhan Liu, Fuyi Li, Chen Li, Tatiana T. Marquez-Lago, André Leier, Tatsuya Akutsu, Geoffrey I. Webb, Dakang Xu, Alexander Ian Smith, Lei Li, Kuo-Chen Chou, Jiangning Song:
Large-scale comparative assessment of computational predictors for lysine post-translational modification sites. Briefings Bioinform. 20(6): 2267-2290 (2019) - [j147]Simone Marini, Francesca Vitali, Sara Rampazzi, Andrea Demartini, Tatsuya Akutsu:
Protease target prediction via matrix factorization. Bioinform. 35(6): 923-929 (2019) - [j146]Jiawei Wang, Jiahui Li, Bingjiao Yang, Ruopeng Xie, Tatiana T. Marquez-Lago, André Leier, Morihiro Hayashida, Tatsuya Akutsu, Yanju Zhang, Kuo-Chen Chou, Joel Selkrig, Tieli Zhou, Jiangning Song, Trevor Lithgow:
Bastion3: a two-layer ensemble predictor of type III secreted effectors. Bioinform. 35(12): 2017-2028 (2019) - [j145]Chun-Yu Lin, Peiying Ruan, Ruiming Li, Jinn-Moon Yang, Simon See, Jiangning Song, Tatsuya Akutsu:
Deep learning with evolutionary and genomic profiles for identifying cancer subtypes. J. Bioinform. Comput. Biol. 17(3): 1940005:1-1940005:15 (2019) - [j144]Teppei Matsubara, Tomoshiro Ochiai, Morihiro Hayashida, Tatsuya Akutsu, Jose C. Nacher:
Convolutional neural network approach to lung cancer classification integrating protein interaction network and gene expression profiles. J. Bioinform. Comput. Biol. 17(3): 1940007:1-1940007:11 (2019) - [j143]Hitoshi Koyano, Morihiro Hayashida, Tatsuya Akutsu:
Optimal string clustering based on a Laplace-like mixture and EM algorithm on a set of strings. J. Comput. Syst. Sci. 106: 94-128 (2019) - [j142]Yuhei Nishiyama, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
Resource Cut, a New Bounding Procedure to Algorithms for Enumerating Tree-Like Chemical Graphs. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 77-90 (2019) - [j141]Tatsuya Akutsu, Avraham A. Melkman:
Identification of the Structure of a Probabilistic Boolean Network From Samples Including Frequencies of Outcomes. IEEE Trans. Neural Networks Learn. Syst. 30(8): 2383-2396 (2019) - 2018
- [j140]Jiangning Song, Fuyi Li, André Leier, Tatiana T. Marquez-Lago, Tatsuya Akutsu, Gholamreza Haffari, Kuo-Chen Chou, Geoffrey I. Webb, Robert N. Pike:
PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy. Bioinform. 34(4): 684-687 (2018) - [j139]Jiawei Wang, Bingjiao Yang, André Leier, Tatiana T. Marquez-Lago, Morihiro Hayashida, Andrea Rocker, Yanju Zhang, Tatsuya Akutsu, Kuo-Chen Chou, Richard A. Strugnell, Jiangning Song, Trevor Lithgow:
Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors. Bioinform. 34(15): 2546-2555 (2018) - [j138]Fuyi Li, Chen Li, Tatiana T. Marquez-Lago, André Leier, Tatsuya Akutsu, Anthony W. Purcell, Alexander Ian Smith, Trevor Lithgow, Roger J. Daly, Jiangning Song, Kuo-Chen Chou:
Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome. Bioinform. 34(24): 4223-4231 (2018) - [j137]Peiying Ruan, Morihiro Hayashida, Tatsuya Akutsu, Jean-Philippe Vert:
Improving prediction of heterodimeric protein complexes using combination with pairwise kernel. BMC Bioinform. 19-S(1): 73-84 (2018) - [j136]Takuya Mori, Hayliang Ngouv, Morihiro Hayashida, Tatsuya Akutsu, Jose C. Nacher:
ncRNA-disease association prediction based on sequence information and tripartite network. BMC Syst. Biol. 12(1): 41-51 (2018) - [j135]Yu Bao, Morihiro Hayashida, Pengyu Liu, Masayuki Ishitsuka, Jose C. Nacher, Tatsuya Akutsu:
Analysis of Critical and Redundant Vertices in Controlling Directed Complex Networks Using Feedback Vertex Sets. J. Comput. Biol. 25(10): 1071-1090 (2018) - [j134]Jinghui Li, Hiroshi Nagamochi, Tatsuya Akutsu:
Enumerating Substituted Benzene Isomers of Tree-Like Chemical Graphs. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 633-646 (2018) - [j133]Takeyuki Tamura, Wei Lu, Jiangning Song, Tatsuya Akutsu:
Computing Minimum Reaction Modifications in a Boolean Metabolic Network. IEEE ACM Trans. Comput. Biol. Bioinform. 15(6): 1853-1862 (2018) - [j132]Avraham A. Melkman, Xiaoqing Cheng, Wai-Ki Ching, Tatsuya Akutsu:
Identifying a Probabilistic Boolean Threshold Network From Samples. IEEE Trans. Neural Networks Learn. Syst. 29(4): 869-881 (2018) - [c85]Tatsuya Akutsu:
Algorithms for Analysis and Control of Boolean Networks. AlCoB 2018: 3-7 - [c84]Chun-Yu Lin, Peiying Ruan, Ruiming Li, Jinn-Moon Yang, Simon See, Tatsuya Akutsu:
Deep Learning with Evolutionary and Genomic Profiles for Identifying Cancer Subtypes. BIBE 2018: 147-150 - [c83]Teppei Matsubara, Tomoshiro Ochiai, Morihiro Hayashida, Tatsuya Akutsu, Jose C. Nacher:
Convolutional Neural Network Approach to Lung Cancer Classification Integrating Protein Interaction Network and Gene Expression Profiles. BIBE 2018: 151-154 - [c82]Morihiro Hayashida, Hitoshi Koyano, Tatsuya Akutsu:
Grammar-based Compression for Directed and Undirected Generalized Series-parallel Graphs using Integer Linear Programming. BIOINFORMATICS 2018: 105-111 - [c81]Tatsuya Akutsu, Colin de la Higuera, Takeyuki Tamura:
A Simple Linear-Time Algorithm for Computing the Centroid and Canonical Form of a Plane Graph and Its Applications. CPM 2018: 10:1-10:12 - [c80]Yuui Tamura, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
Enumerating Chemical Mono-Block 3-Augmented Trees with Two Junctions. ICBBB 2018: 48-55 - [c79]Tatsuya Akutsu, Jesper Jansson, Ruiming Li, Atsuhiro Takasu, Takeyuki Tamura:
New and Improved Algorithms for Unordered Tree Inclusion. ISAAC 2018: 27:1-27:12 - 2017
- [j131]Xiaoqing Cheng, Takeyuki Tamura, Wai-Ki Ching, Tatsuya Akutsu:
Discrimination of singleton and periodic attractors in Boolean networks. Autom. 84: 205-213 (2017) - [j130]Yuki Kato, Tomoya Mori, Kengo Sato, Shingo Maegawa, Hiroshi Hosokawa, Tatsuya Akutsu:
An accessibility-incorporated method for accurate prediction of RNA-RNA interactions from sequence data. Bioinform. 33(2): 202-209 (2017) - [j129]Tatsuya Akutsu:
Selected Papers from the 16th International Conference on Bioinformatics (InCoB 2017). J. Bioinform. Comput. Biol. 15(5): 1702003:1-1702003:2 (2017) - [j128]Tatsuya Akutsu, Jesper Jansson, Atsuhiro Takasu, Takeyuki Tamura:
On the parameterized complexity of associative and commutative unification. Theor. Comput. Sci. 660: 57-74 (2017) - [i2]Tatsuya Akutsu, Jesper Jansson, Ruiming Li, Atsuhiro Takasu, Takeyuki Tamura:
New Algorithms for Unordered Tree Inclusion. CoRR abs/1712.05517 (2017) - 2016
- [j127]Wenpin Hou, Takeyuki Tamura, Wai-Ki Ching, Tatsuya Akutsu:
Finding and Analyzing the Minimum Set of Driver Nodes in control of Boolean Networks. Adv. Complex Syst. 19(3): 1650006:1-1650006:32 (2016) - [j126]Chen Li, Catherine Ching Han Chang, Jeremy Nagel, Benjamin T. Porebski, Morihiro Hayashida, Tatsuya Akutsu, Jiangning Song, Ashley M. Buckle:
Critical evaluation of in silico methods for prediction of coiled-coil domains in proteins. Briefings Bioinform. 17(2): 270-282 (2016) - [j125]Jira Jindalertudomdee, Morihiro Hayashida, Yang Zhao, Tatsuya Akutsu:
Enumeration method for tree-like chemical compounds with benzene rings and naphthalene rings by breadth-first search order. BMC Bioinform. 17: 113 (2016) - [j124]