| PrDOS: prediction of disordered protein regions from amino acid sequence T Ishida, K Kinoshita Nucleic acids research 35 (suppl_2), W460-W464, 2007 | 899 | 2007 |
| D2P2: database of disordered protein predictions ME Oates, P Romero, T Ishida, M Ghalwash, MJ Mizianty, B Xue, ... Nucleic acids research 41 (D1), D508-D516, 2013 | 701 | 2013 |
| Prediction of disordered regions in proteins based on the meta approach T Ishida, K Kinoshita Bioinformatics 24 (11), 1344-1348, 2008 | 292 | 2008 |
| Community-wide assessment of protein-interface modeling suggests improvements to design methodology SJ Fleishman, TA Whitehead, EM Strauch, JE Corn, S Qin, HX Zhou, ... Journal of molecular biology 414 (2), 289-302, 2011 | 157 | 2011 |
| MEGADOCK 4.0: an ultra–high-performance protein–protein docking software for heterogeneous supercomputers M Ohue, T Shimoda, S Suzuki, Y Matsuzaki, T Ishida, Y Akiyama Bioinformatics 30 (22), 3281-3283, 2014 | 103 | 2014 |
| GHOSTX: an improved sequence homology search algorithm using a query suffix array and a database suffix array S Suzuki, M Kakuta, T Ishida, Y Akiyama PloS one 9 (8), e103833, 2014 | 101 | 2014 |
| MEGADOCK: an all-to-all protein-protein interaction prediction system using tertiary structure data M Ohue, Y Matsuzaki, N Uchikoga, T Ishida, Y Akiyama Protein and peptide letters 21 (8), 766-778, 2014 | 83 | 2014 |
| Identification of transient hub proteins and the possible structural basis for their multiple interactions M Higurashi, T Ishida, K Kinoshita Protein Science 17 (1), 72-78, 2008 | 80 | 2008 |
| PiSite: a database of protein interaction sites using multiple binding states in the PDB M Higurashi, T Ishida, K Kinoshita Nucleic acids research 37 (suppl_1), D360-D364, 2009 | 62 | 2009 |
| Faster sequence homology searches by clustering subsequences S Suzuki, M Kakuta, T Ishida, Y Akiyama Bioinformatics 31 (8), 1183-1190, 2015 | 56 | 2015 |
| Highly precise protein-protein interaction prediction based on consensus between template-based and de novo docking methods M Ohue, Y Matsuzaki, T Shimoda, T Ishida, Y Akiyama BMC proceedings 7 (Suppl 7), S6, 2013 | 46 | 2013 |
| Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target S Chiba, K Ikeda, T Ishida, MM Gromiha, YH Taguchi, M Iwadate, ... Scientific reports 5 (1), 1-13, 2015 | 45 | 2015 |
| Protein model accuracy estimation based on local structure quality assessment using 3D convolutional neural network R Sato, T Ishida PloS one 14 (9), e0221347, 2019 | 39 | 2019 |
| GHOSTM: a GPU-accelerated homology search tool for metagenomics S Suzuki, T Ishida, K Kurokawa, Y Akiyama PloS one 7 (5), e36060, 2012 | 34 | 2012 |
| Extreme Big Data (EBD): Next generation big data infrastructure technologies towards yottabyte/year S Matsuoka, H Sato, O Tatebe, M Koibuchi, I Fujiwara, S Suzuki, M Kakuta, ... Supercomputing frontiers and innovations 1 (2), 89-107, 2014 | 33 | 2014 |
| An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes S Chiba, T Ishida, K Ikeda, M Mochizuki, R Teramoto, YH Taguchi, ... Scientific reports 7 (1), 1-13, 2017 | 32 | 2017 |
| MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments. Y Matsuzaki, N Uchikoga, M Ohue, T Shimoda, T Sato, T Ishida, ... Source code for biology and medicine 8, 18, 2013 | 32 | 2013 |
| Development of an ab initio protein structure prediction system ABLE T Ishida, T Nishimura, M Nozaki, T Inoue, T Terada, S Nakamura, ... Genome Informatics 14, 228-237, 2003 | 27 | 2003 |
| Sequence alignment using machine learning for accurate template-based protein structure prediction S Makigaki, T Ishida Bioinformatics 36 (1), 104-111, 2020 | 26 | 2020 |
| In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease R Yoshino, N Yasuo, Y Hagiwara, T Ishida, DK Inaoka, Y Amano, ... Scientific reports 7 (1), 1-9, 2017 | 26 | 2017 |
