T
Tetsuo Sato
Researcher at Nara Institute of Science and Technology
Publications - 48
Citations - 320
Tetsuo Sato is an academic researcher from Nara Institute of Science and Technology. The author has contributed to research in topics: Diffusion MRI & Tractography. The author has an hindex of 9, co-authored 48 publications receiving 276 citations. Previous affiliations of Tetsuo Sato include Gunma Prefectural College of Health Sciences.
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Journal ArticleDOI
KNApSAcK Metabolite Activity Database for Retrieving the Relationships Between Metabolites and Biological Activities
Yukiko Nakamura,Farit Mochamad Afendi,Aziza Kawsar Parvin,Naoaki Ono,Ken Tanaka,Aki Hirai Morita,Tetsuo Sato,Tadao Sugiura,Altaf-Ul-Amin,Shigehiko Kanaya +9 more
TL;DR: The KNApSAcK Metabolite Activity DB is integrated within the KNAcK Family DBs to facilitate further systematized research in various omics fields, especially metabolomics, nutrigenomics and foodomics.
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Development and Mining of a Volatile Organic Compound Database
Azian Azamimi Abdullah,Md. Altaf-Ul-Amin,Naoaki Ono,Tetsuo Sato,Tadao Sugiura,Aki Hirai Morita,Tetsuo Katsuragi,Ai Muto,Takaaki Nishioka,Shigehiko Kanaya +9 more
TL;DR: KNApSAcK Metabolite Ecology Database is developed, which contains the information on the relationships between VOCs and their emitting organisms, and is linked with the KNApsacK Core and K NApSA cK Metabolic Activity Database to provide further information onThe metabolites and their biological activities.
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An integrative network-based approach to identify novel disease genes and pathways: a case study in the context of inflammatory bowel disease.
Ryohei Eguchi,Mohammand Bozlul Karim,Pingzhao Hu,Tetsuo Sato,Tetsuo Sato,Naoaki Ono,Shigehiko Kanaya,Md. Altaf-Ul-Amin +7 more
TL;DR: An approach to identify novel disease genes and pathways by integrating information of differential gene expression, protein-protein interaction and known disease genes related to IBD is presented and can be generalized to find disease-associated genes for other diseases.
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Supervised clustering based on DPClusO: prediction of plant-disease relations using Jamu formulas of KNApSAcK database.
Sony Hartono Wijaya,Husnawati Husnawati,Farit Mochamad Afendi,Irmanida Batubara,Latifah Kosim Darusman,Altaf-Ul-Amin,Tetsuo Sato,Naoaki Ono,Tadao Sugiura,Shigehiko Kanaya +9 more
TL;DR: The plant to disease relations predicted by the proposed new approach to predict the relation between plant and disease using network analysis and supervised clustering were found to produce around 90% successful predictions.
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A Glimpse to Background and Characteristics of Major Molecular Biological Networks
TL;DR: This review briefly discusses both the biological background and topological properties of major types of omics networks to facilitate a comprehensive understanding and to conceptualize the foundation of network biology.