Yasunari Matsuzaka - Concepedia

Author

Yasunari Matsuzaka

Tokai University

Also Known As

Matsuzaka, Y., Matsuzaka, Yasunari, Y. Matsuzaka, Yasunari Matsuzaka

Publications

1.2K

Citations

H-Index

114

Concepts

All Affiliations

Tokai University Meiji Pharmaceutical University National Center of Neurology and Psychiatry The University of Tokyo Murdoch University

About

Yasunari Matsuzaka is an author at Tokai University specializing in medicine, engineering, and deep learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Medicine	14	17	564
2	Engineering	8	8	239
3	Natural Sciences	2	2	70
4	Health Sciences	1	1	19
5	Biochemistry	1	1	38

Yasunari Matsuzaka

Publications

855

Citations

H-Index

Page 1

	Year	Citations
Three novel serum biomarkers, miR-1, miR-133a, and miR-206 for Limb-girdle muscular dystrophy, Facioscapulohumeral muscular dystrophy, and Becker muscular dystrophy Yasunari Matsuzaka, Soichiro Kishi, Yoshitsugu Aoki, Environmental Health and Preventive Medicine	2014	88
SLURP-2, a novel member of the human Ly-6 superfamily that is up-regulated in psoriasis vulgaris☆☆Sequence data from this article have been deposited with the DDBJ/EMBL/GenBank Data Libraries under Accession No. AB081838. Hitomi Tsuji, Koichi Okamoto, Yasunari Matsuzaka, Genomics Translational BiologyMedicineGeneticsPathogenesisPsoriatic Arthritis	2003	85
AI-Based Computer Vision Techniques and Expert Systems Yasunari Matsuzaka, Ryu Yashiro AI Artificial IntelligenceConvolutional Neural NetworkEngineeringMachine LearningImage Recognition (Computer Vision)	2023	68
Characterization and Functional Analysis of Extracellular Vesicles and Muscle-Abundant miRNAs (miR-1, miR-133a, and miR-206) in C2C12 Myocytes and mdx Mice Yasunari Matsuzaka, Jun Tanihata, Hirofumi Komaki, PLoS ONE PathologyCell DeathExtracellular MicrovesiclesCreatine KinaseCellular Physiology	2016	66
Optimization of a Deep-Learning Method Based on the Classification of Images Generated by Parameterized Deep Snap a Novel Molecular-Image-Input Technique for Quantitative Structure–Activity Relationship (QSAR) Analysis Yasunari Matsuzaka, Yoshihiro Uesawa Frontiers in Bioengineering and Biotechnology Drug TargetEngineeringMachine LearningQuantitative Structure–activity RelationshipDeep-learning Method	2019	46
Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library Yasunari Matsuzaka, Yoshihiro Uesawa International Journal of Molecular Sciences Drug TargetCompound LibraryChemical BiologySystems PharmacologyMedicinal Chemistry	2019	38
Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap–Deep Learning Yasunari Matsuzaka, Takuomi Hosaka, Anna Ogaito, Molecules	2020	35
Identification of novel candidate genes in the diffuse panbronchiolitis critical region of the class I human MHC Yasunari Matsuzaka, Kenichi Tounai, Akihiro Denda, Immunogenetics HistocompatibilityImmunogeneticsAutoimmune DiseaseNovel Candidate GenesDisease Mechanism	2002	33
Identification, expression analysis and polymorphism of a novel RLTPR gene encoding a RGD motif, tropomodulin domain and proline/leucine-rich regions Yasunari Matsuzaka, Koichi Okamoto, Tomotaka Mabuchi, Gene Signal TransductionProtein ExpressionMedicineGeneticsNatural Sciences	2004	32
Current Strategies and Therapeutic Applications of Mesenchymal Stem Cell-Based Drug Delivery Yasunari Matsuzaka, Ryu Yashiro Pharmaceuticals Tissue EngineeringCell TherapyEngineeringImmunologyBiomedical Engineering	2024	30

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