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Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network

Molecular informatics, 2022-07, Vol.41 (7), p.e2100247-n/a

2022

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BiClusO: A Novel Biclustering Approach and Its Application to Species-VOC Relational Data

IEEE/ACM transactions on computational biology and bioinformatics, 2020-11, Vol.17 (6), p.1955-1965

2020

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Comprehensive Exploration of Target‐specific Ligands Using a Graph Convolution Neural Network

Molecular informatics, 2020-01, Vol.39 (1-2), p.e1900095-n/a

2020

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Development and implementation of an algorithm for detection of protein complexes in large interaction networks

BMC bioinformatics, 2006-04, Vol.7 (1), p.207-207, Article 207

2006

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Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

Molecular informatics, 2021-02, Vol.40 (2), p.e2000203-n/a

2021

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Metabolomic Studies of Indonesian Jamu Medicines: Prediction of Jamu Efficacy and Identification of Important Metabolites

Molecular informatics, 2017-12, Vol.36 (12), p.n/a

2017

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A system biology approach based on metabolic biomarkers and protein–protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

Scientific reports, 2021-07, Vol.11 (1), p.14450-11, Article 14450

2021

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Materials Data-science Approach for Comprehensive Understanding of Organic Thin Film Solar Cells

Journal of Computer Aided Chemistry, 2023, Vol.23, pp.8-24

2023

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Data Science for QSAR for Protease activity

Journal of Computer Aided Chemistry, 2023, Vol.23, pp.43-49

2023

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Molecular Graph Indexes for Assessing Heterogeneity of Chemical Compounds

Journal of Computer Aided Chemistry, 2023, Vol.23, pp.50-59

2023

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Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach

PeerJ (San Francisco, CA), 2021-08, Vol.9, p.e11876-e11876, Article e11876

2021

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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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Systems Biology in the Context of Big Data and Networks

BioMed research international, 2014-01, Vol.2014 (2014), p.1-11

2014

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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

BMC bioinformatics, 2018-07, Vol.19 (1), p.264-264, Article 264

2018

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A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

BioMed research international, 2016-01, Vol.2016 (2016), p.1-17

2016

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[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]DPClusOST: A Software Tool for General Purpose Graph Clustering

Journal of Computer Aided Chemistry, 2017, Vol.18, pp.76-93

2017

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Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm

Plant methods, 2022-11, Vol.18 (1), p.1-118, Article 118

2022

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A Novel CNN-Based Framework for Classification of Signal Quality and Sleep Position from a Capacitive ECG Measurement

Sensors (Basel, Switzerland), 2019-04, Vol.19 (7), p.1731

2019

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Sequence-specific error profile of Illumina sequencers

Nucleic acids research, 2011-07, Vol.39 (13), p.e90-e90

2011

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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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The feasibility of predicting impending malignant ventricular arrhythmias by using nonlinear features of short heartbeat intervals

Computer methods and programs in biomedicine, 2021-06, Vol.205, p.106102-106102, Article 106102

2021

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On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

Frontiers in physiology, 2023-05, Vol.14, p.1156286

2023

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Kinematics approach with neural networks for early detection of sepsis (KANNEDS)

BMC medical informatics and decision making, 2021-05, Vol.21 (1), p.163-163, Article 163

2021

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[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]Centrality Values of Yeast Proteins in a PPI Network Are Related to Their Essentiality and Functions

Journal of Computer Aided Chemistry, 2017, Vol.18, pp.94-109

2017

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An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data

BioMed research international, 2014-01, Vol.2014 (2014), p.1-8

2014

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Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network

BiClusO: A Novel Biclustering Approach and Its Application to Species-VOC Relational Data

Comprehensive Exploration of Target‐specific Ligands Using a Graph Convolution Neural Network

Development and implementation of an algorithm for detection of protein complexes in large interaction networks

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning

Metabolomic Studies of Indonesian Jamu Medicines: Prediction of Jamu Efficacy and Identification of Important Metabolites

A system biology approach based on metabolic biomarkers and protein–protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

Materials Data-science Approach for Comprehensive Understanding of Organic Thin Film Solar Cells

Data Science for QSAR for Protease activity

Molecular Graph Indexes for Assessing Heterogeneity of Chemical Compounds

Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach

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

Systems Biology in the Context of Big Data and Networks

An integrative network-based approach to identify novel disease genes and pathways: a case study in the context of inflammatory bowel disease

A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]DPClusOST: A Software Tool for General Purpose Graph Clustering

Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm

A Novel CNN-Based Framework for Classification of Signal Quality and Sleep Position from a Capacitive ECG Measurement

Sequence-specific error profile of Illumina sequencers

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

The feasibility of predicting impending malignant ventricular arrhythmias by using nonlinear features of short heartbeat intervals

On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

Kinematics approach with neural networks for early detection of sepsis (KANNEDS)

[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]Centrality Values of Yeast Proteins in a PPI Network Are Related to Their Essentiality and Functions

An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data

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