Kana Shimizu
Kana Shimizu
Waseda University, National Institute of Advanced Industrial Science and Technology
Verified email at - Homepage
Cited by
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POODLE-L: a two-level SVM prediction system for reliably predicting long disordered regions
S Hirose, K Shimizu, S Kanai, Y Kuroda, T Noguchi
Bioinformatics 23 (16), 2046-2053, 2007
POODLE-S: web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix
K Shimizu, S Hirose, T Noguchi
Bioinformatics 23 (17), 2337-2338, 2007
ANGLE: a sequencing errors resistant program for predicting protein coding regions in unfinished cDNA
K Shimizu, J Adachi, Y Muraoka
Journal of Bioinformatics and Computational Biology 4 (03), 649-664, 2006
Efficient privacy-preserving string search and an application in genomics
K Shimizu, K Nuida, G Rätsch
Bioinformatics 32 (11), 1652-1661, 2016
Interaction between intrinsically disordered proteins frequently occurs in a human protein–protein interaction network
K Shimizu, H Toh
Journal of molecular biology 392 (5), 1253-1265, 2009
Predicting mostly disordered proteins by using structure-unknown protein data
K Shimizu, Y Muraoka, S Hirose, K Tomii, T Noguchi
BMC bioinformatics 8, 1-15, 2007
Differentially private bayesian learning on distributed data
M Heikkilä, E Lagerspetz, S Kaski, K Shimizu, S Tarkoma, A Honkela
Advances in neural information processing systems 30, 2017
PoSSuM: a database of similar protein–ligand binding and putative pockets
JI Ito, Y Tabei, K Shimizu, K Tsuda, K Tomii
Nucleic acids research 40 (D1), D541-D548, 2012
Search system, search method, and program
K Iwamura, T Hirokawa, K Tsuda, H Arai, J Sakuma, K Asai, M Hamada, ...
US Patent 9,215,068, 2015
Privacy-preserving string search for genome sequences with fhe bootstrapping optimization
Y Ishimaki, H Imabayashi, K Shimizu, H Yamana
2016 IEEE International Conference on Big Data (Big Data), 3989-3991, 2016
PDB‐scale analysis of known and putative ligand‐binding sites with structural sketches
JI Ito, Y Tabei, K Shimizu, K Tomii, K Tsuda
Proteins: Structure, Function, and Bioinformatics 80 (3), 747-763, 2012
Differentially private cross-silo federated learning
MA Heikkilä, A Koskela, K Shimizu, S Kaski, A Honkela
arXiv preprint arXiv:2007.05553, 2020
SlideSort: all pairs similarity search for short reads
K Shimizu, K Tsuda
Bioinformatics 27 (4), 464-470, 2011
Efficient two-level homomorphic encryption in prime-order bilinear groups and a fast implementation in webassembly
N Attrapadung, G Hanaoka, S Mitsunari, Y Sakai, K Shimizu, T Teruya
Proceedings of the 2018 on Asia Conference on Computer and Communications …, 2018
POODLE-I: disordered region prediction by integrating POODLE series and structural information predictors based on a workflow approach
S Hirose, K Shimizu, T Noguchi
In silico biology 10 (3-4), 185-191, 2010
Privacy-preserving search for chemical compound databases
K Shimizu, K Nuida, H Arai, S Mitsunari, N Attrapadung, M Hamada, ...
BMC bioinformatics 16, 1-14, 2015
Secure wavelet matrix: Alphabet-friendly privacy-preserving string search for bioinformatics
H Sudo, M Jimbo, K Nuida, K Shimizu
IEEE/ACM transactions on computational biology and bioinformatics 16 (5 …, 2018
Discovery of cryoprotective activity in human genome-derived intrinsically disordered proteins
N Matsuo, N Goda, K Shimizu, S Fukuchi, M Ota, H Hiroaki
International journal of molecular sciences 19 (2), 401, 2018
A method for systematic assessment of intrinsically disordered protein regions by NMR
N Goda, K Shimizu, Y Kuwahara, T Tenno, T Noguchi, T Ikegami, M Ota, ...
International journal of molecular sciences 16 (7), 15743-15760, 2015
SAHG, a comprehensive database of predicted structures of all human proteins
C Motono, J Nakata, R Koike, K Shimizu, M Shirota, T Amemiya, K Tomii, ...
Nucleic acids research 39 (suppl_1), D487-D493, 2011
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