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Tomoyuki Miyao
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2020 – today
- 2024
- [j14]Itsuki Maeda
, Shunsuke Tamura
, Yoshihiro Ogura, Takayuki Serizawa, Takashi Shimada
, Ryo Kunimoto
, Tomoyuki Miyao
:
Scaffold-Hopped Compound Identification by Ligand-Based Approaches with a Prospective Affinity Test. J. Chem. Inf. Model. 64(14): 5557-5569 (2024) - 2023
- [j13]Shunsuke Tamura, Tomoyuki Miyao, Jürgen Bajorath:
Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity. J. Cheminformatics 15(1): 4 (2023) - [c1]Haixin Wang
, Jian Yang
, Ryohei Katayama
, Michiya Matsusaki
, Tomoyuki Miyao
, Jinjia Zhou
:
NuclSeg: nuclei segmentation using semi-supervised stain deconvolution. MMAsia 2023: 22:1-22:6 - 2022
- [j12]Itsuki Maeda
, Akinori Sato
, Shunsuke Tamura
, Tomoyuki Miyao
:
Ligand-based approaches to activity prediction for the early stage of structure-activity-relationship progression. J. Comput. Aided Mol. Des. 36(3): 237-252 (2022) - 2021
- [j11]Akinori Sato
, Tomoyuki Miyao, Swarit Jasial
, Kimito Funatsu
:
Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations. J. Comput. Aided Mol. Des. 35(2): 179-193 (2021) - [j10]Hiroshi Nakano
, Tomoyuki Miyao
, Swarit Jasial
, Kimito Funatsu
:
Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping. J. Chem. Inf. Model. 61(7): 3348-3360 (2021) - 2020
- [j9]Hiroshi Nakano
, Tomoyuki Miyao
, Kimito Funatsu
:
Exploring Topological Pharmacophore Graphs for Scaffold Hopping. J. Chem. Inf. Model. 60(4): 2073-2081 (2020)
2010 – 2019
- 2019
- [j8]Tomoyuki Miyao
, Swarit Jasial
, Jürgen Bajorath
, Kimito Funatsu
:
Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships. J. Comput. Aided Mol. Des. 33(8): 729-743 (2019) - [j7]Tomoyuki Miyao, Kimito Funatsu
, Jürgen Bajorath
:
Exploring Alternative Strategies for the Identification of Potent Compounds Using Support Vector Machine and Regression Modeling. J. Chem. Inf. Model. 59(3): 983-992 (2019) - [j6]Tomoyuki Miyao, Kimito Funatsu
, Jürgen Bajorath
:
Three-Dimensional Activity Landscape Models of Different Design and Their Application to Compound Mapping and Potency Prediction. J. Chem. Inf. Model. 59(3): 993-1004 (2019) - [j5]Tomoyuki Miyao
, Kimito Funatsu
:
Iterative Screening Methods for Identification of Chemical Compounds with Specific Values of Various Properties. J. Chem. Inf. Model. 59(6): 2626-2641 (2019) - [j4]Shunsuke Tamura
, Tomoyuki Miyao
, Kimito Funatsu
:
Development of R-Group Fingerprints Based on the Local Landscape from an Attachment Point of a Molecular Structure. J. Chem. Inf. Model. 59(6): 2656-2663 (2019) - 2018
- [j3]Tomoyuki Miyao, Jürgen Bajorath
:
Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching. J. Comput. Aided Mol. Des. 32(7): 759-767 (2018) - 2017
- [i1]Tomoyuki Miyao, Kimito Funatsu, Jürgen Bajorath
:
Exploring differential evolution for inverse QSAR analysis. F1000Research 6: 1285- (2017) - 2016
- [j2]Tomoyuki Miyao, Hiromasa Kaneko, Kimito Funatsu:
Ring system-based chemical graph generation for de novo molecular design. J. Comput. Aided Mol. Des. 30(5): 425-446 (2016) - [j1]Tomoyuki Miyao, Hiromasa Kaneko, Kimito Funatsu:
Inverse QSPR/QSAR Analysis for Chemical Structure Generation (from y to x). J. Chem. Inf. Model. 56(2): 286-299 (2016)
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last updated on 2024-08-23 19:28 CEST by the dblp team
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