Takashi Ishida
Takashi Ishida
Department of Computer Science, School of Computing, Tokyo
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PrDOS: prediction of disordered protein regions from amino acid sequence
T Ishida, K Kinoshita
Nucleic acids research 35 (suppl_2), W460-W464, 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
Prediction of disordered regions in proteins based on the meta approach
T Ishida, K Kinoshita
Bioinformatics 24 (11), 1344-1348, 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
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
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
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
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
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
Faster sequence homology searches by clustering subsequences
S Suzuki, M Kakuta, T Ishida, Y Akiyama
Bioinformatics 31 (8), 1183-1190, 2015
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
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
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
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
GHOSTM: a GPU-accelerated homology search tool for metagenomics
S Suzuki, T Ishida, K Kurokawa, Y Akiyama
PloS one 7 (5), e36060, 2012
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
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
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
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
Sequence alignment using machine learning for accurate template-based protein structure prediction
S Makigaki, T Ishida
Bioinformatics 36 (1), 104-111, 2020
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