| Identification of genetic networks from a small number of gene expression patterns under the Boolean network model T Akutsu, S Miyano, S Kuhara Biocomputing'99, 17-28, 1999 | 1065 | 1999 |
| Control of Boolean networks: Hardness results and algorithms for tree structured networks T Akutsu, M Hayashida, WK Ching, MK Ng Journal of theoretical biology 244 (4), 670-679, 2007 | 614 | 2007 |
| Inferring qualitative relations in genetic networks and metabolic pathways T Akutsu, S Miyano, S Kuhara Bioinformatics 16 (8), 727-734, 2000 | 542 | 2000 |
| Protein homology detection using string alignment kernels H Saigo, JP Vert, N Ueda, T Akutsu Bioinformatics 20 (11), 1682-1689, 2004 | 503 | 2004 |
| Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots T Akutsu Discrete Applied Mathematics 104 (1-3), 45-62, 2000 | 443 | 2000 |
| Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics): Preface PK Agarwal, T Akutsu, A Amihood, A Apostolico, C Benham, G Benson, ... Lecture notes in computer science (including subseries lecture notes in …, 2005 | 426* | 2005 |
| iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data Z Chen, P Zhao, F Li, TT Marquez-Lago, A Leier, J Revote, Y Zhu, ... Briefings in bioinformatics 21 (3), 1047-1057, 2020 | 419 | 2020 |
| PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites J Song, H Tan, AJ Perry, T Akutsu, GI Webb, JC Whisstock, RN Pike PloS one 7 (11), e50300, 2012 | 357 | 2012 |
| IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming K Sato, Y Kato, M Hamada, T Akutsu, K Asai Bioinformatics 27 (13), i85-i93, 2011 | 347 | 2011 |
| Extensions of marginalized graph kernels P Mahé, N Ueda, T Akutsu, JL Perret, JP Vert Proceedings of the twenty-first international conference on Machine learning, 70, 2004 | 304 | 2004 |
| Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function T Akutsu, S Miyano, S Kuhara Proceedings of the fourth annual international conference on Computational …, 2000 | 264 | 2000 |
| Graph kernels for molecular structure− activity relationship analysis with support vector machines P Mahé, N Ueda, T Akutsu, JL Perret, JP Vert Journal of chemical information and modeling 45 (4), 939-951, 2005 | 252 | 2005 |
| iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization Z Chen, P Zhao, C Li, F Li, D Xiang, YZ Chen, T Akutsu, RJ Daly, GI Webb, ... Nucleic acids research 49 (10), e60-e60, 2021 | 246 | 2021 |
| iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites J Song, Y Wang, F Li, T Akutsu, ND Rawlings, GI Webb, KC Chou Briefings in bioinformatics 20 (2), 638-658, 2019 | 231 | 2019 |
| Dominating scale-free networks with variable scaling exponent: heterogeneous networks are not difficult to control JC Nacher, T Akutsu New Journal of Physics 14 (7), 073005, 2012 | 203 | 2012 |
| A novel representation of protein sequences for prediction of subcellular location using support vector machines S Matsuda, JP Vert, H Saigo, N Ueda, H Toh, T Akutsu Protein Science 14 (11), 2804-2813, 2005 | 198 | 2005 |
| Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions T Akutsu, S Kuhara, O Maruyama, S Miyano Genome Informatics 8, 254-255, 1997 | 194 | 1997 |
| A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction S Mei, F Li, A Leier, TT Marquez-Lago, K Giam, NP Croft, T Akutsu, ... Briefings in bioinformatics 21 (4), 1119-1135, 2020 | 193 | 2020 |
| A system for identifying genetic networks from gene expression patterns produced by gene disruptions and overexpressions T Akutsu, S Kuhara, O Maruyama, S Miyano Genome Informatics 9, 151-160, 1998 | 192 | 1998 |
| Cascleave: towards more accurate prediction of caspase substrate cleavage sites J Song, H Tan, H Shen, K Mahmood, SE Boyd, GI Webb, T Akutsu, ... Bioinformatics 26 (6), 752-760, 2010 | 184 | 2010 |
