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Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks

BMC bioinformatics, 2019-07, Vol.20 (1), p.380-380, Article 380

2019

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Classification of metabolites by metabolic pathways concerning terpenoids, phenylpropanoids, and polyketide compounds based on machine learning

Journal of Computer Aided Chemistry, 2023, Vol.23, pp.25-34

2023

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KNApSAcK Family Databases: Integrated Metabolite-Plant Species Databases for Multifaceted Plant Research

Plant and cell physiology, 2012-02, Vol.53 (2), p.e1-e1

2012

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Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities

Molecular informatics, 2014-12, Vol.33 (11-12), p.790-801

2014

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[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]Classification of Alkaloid Compounds Based on Subring Skeleton (SRS) Profiling: On Finding Relationship of Compounds with Metabolic Pathways

Journal of Computer Aided Chemistry, 2017, Vol.18, pp.58-75

2017

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KNApSAcK Metabolite Activity Database for retrieving the relationships between metabolites and biological activities

Plant and cell physiology, 2014-01, Vol.55 (1), p.e7-e7

2014

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Utilization of KNApSAcK Family Databases for Developing Herbal Medicine Systems

Journal of Computer Aided Chemistry, 2016, Vol.17, pp.1-7

2016

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KNApSAcK-3D: a three-dimensional structure database of plant metabolites

Plant and cell physiology, 2013-02, Vol.54 (2), p.e4-e4

2013

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Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

Computational and structural biotechnology journal, 2013-01, Vol.4 (5), p.e201301010-e201301010, Article e201301010

2013

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Development and Mining of a Volatile Organic Compound Database

BioMed research international, 2015-01, Vol.2015, p.139254-13

2015

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Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database

Plant and cell physiology, 2013-05, Vol.54 (5), p.711-727

2013

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Predicting and considering properties of general polymers using incomplete dataset

2020 International Symposium on Semiconductor Manufacturing (ISSM), 2020, p.1-3

2020

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Cutting Edge Data Science towards Understanding of Crude Drug, Food and Ecosystem Based on Metabolomics

KAGAKU TO SEIBUTSU, 2015/08/20, Vol.53(9), pp.600-607

2015

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Cutting Edge Data Science towards Understanding of Crude Drug, Food and Ecosystem Based on Metabolomics: 医食同源と生態学の体系化に向けて

Kagaku To Seibutsu, 2015, Vol.53 (9), p.600-607

2015

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Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

Computational and structural biotechnology journal, 2013-01, Vol.4 (5), p.e201301010

2013

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ビッグ・データ・バイオロジー: 医食同源と生態学の体系化に向けて

化学と生物, 2015/08/20, Vol.53(9), pp.600-607

2015

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Data Intensive Study of Accessibility of Edible Species and Healthcare Across the Globe

Japanese Journal of Complementary and Alternative Medicine, 2018/03/31, Vol.15(1), pp.37-60

2018

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Databases for Natural Product Research

Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, 2013

2013

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Hyperfructosemia in sleep disordered breathing: metabolome analysis of Nagahama study

Scientific reports, 2023-08, Vol.13 (1), p.12735-12735, Article 12735

2023

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Effect of deep learning-based reconstruction on high-resolution three-dimensional T2-weighted fast asymmetric spin-echo imaging in the preoperative evaluation of cerebellopontine angle tumors

Neuroradiology, 2024-07, Vol.66 (7), p.1123-1130

2024

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Plant Sciences
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Clustering
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Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks

Classification of metabolites by metabolic pathways concerning terpenoids, phenylpropanoids, and polyketide compounds based on machine learning

KNApSAcK Family Databases: Integrated Metabolite-Plant Species Databases for Multifaceted Plant Research

Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities

[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]Classification of Alkaloid Compounds Based on Subring Skeleton (SRS) Profiling: On Finding Relationship of Compounds with Metabolic Pathways

KNApSAcK Metabolite Activity Database for retrieving the relationships between metabolites and biological activities

Utilization of KNApSAcK Family Databases for Developing Herbal Medicine Systems

KNApSAcK-3D: a three-dimensional structure database of plant metabolites

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

Development and Mining of a Volatile Organic Compound Database

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database

Predicting and considering properties of general polymers using incomplete dataset

Cutting Edge Data Science towards Understanding of Crude Drug, Food and Ecosystem Based on Metabolomics

Cutting Edge Data Science towards Understanding of Crude Drug, Food and Ecosystem Based on Metabolomics: 医食同源と生態学の体系化に向けて

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

ビッグ・データ・バイオロジー: 医食同源と生態学の体系化に向けて

Data Intensive Study of Accessibility of Edible Species and Healthcare Across the Globe

Databases for Natural Product Research

Hyperfructosemia in sleep disordered breathing: metabolome analysis of Nagahama study

Effect of deep learning-based reconstruction on high-resolution three-dimensional T2-weighted fast asymmetric spin-echo imaging in the preoperative evaluation of cerebellopontine angle tumors

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