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A new advanced in silico drug discovery method for novel coronavirus (SARS-CoV-2) with tensor decomposition-based unsupervised feature extraction

PloS one, 2020-09, Vol.15 (9), p.e0238907-e0238907

2020

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Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets

Scientific reports, 2017-10, Vol.7 (1), p.13733-16, Article 13733

Taguchi, Y.-h.

2017

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Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes

BMC bioinformatics, 2018-05, Vol.19 (Suppl 4), p.99-99, Article 99

Taguchi, Y-H

2018

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Drug candidate identification based on gene expression of treated cells using tensor decomposition-based unsupervised feature extraction for large-scale data

BMC bioinformatics, 2019-02, Vol.19 (Suppl 13), p.388-388, Article 388

Taguchi, Y-H

2019

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Tensor decomposition-based unsupervised feature extraction applied to matrix products for multi-view data processing

PloS one, 2017-08, Vol.12 (8), p.e0183933-e0183933

2017

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Features extracted using tensor decomposition reflect the biological features of the temporal patterns of human blood multimodal metabolome

PloS one, 2023-02, Vol.18 (2), p.e0281594-e0281594

2023

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Identification of genes associated with altered gene expression and m6A profiles during hypoxia using tensor decomposition based unsupervised feature extraction

Scientific reports, 2021-04, Vol.11 (1), p.8909-8909, Article 8909

2021

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PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Scientific reports, 2021-08, Vol.11 (1), p.17351-17351, Article 17351

2021

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Unsupervised tensor decomposition-based method to extract candidate transcription factors as histone modification bookmarks in post-mitotic transcriptional reactivation

PloS one, 2021-05, Vol.16 (5), p.e0251032-e0251032

2021

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Bioinformatic tools for epitranscriptomics

American Journal of Physiology: Cell Physiology, 2023-02, Vol.324 (2), p.C447-C457

Taguchi, Y-H

2023

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Exploring microRNA Biomarker for Amyotrophic Lateral Sclerosis

International journal of molecular sciences, 2018-04, Vol.19 (5), p.1318

2018

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Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more suitable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods

Genomics (San Diego, Calif.), 2023-03, Vol.115 (2), p.110577-110577, Article 110577

2023

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Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection tools

PloS one, 2022-09, Vol.17 (9), p.e0275472-e0275472

2022

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Tensor decomposition discriminates tissues using scATAC-seq

Biochimica et biophysica acta. General subjects, 2023-06, Vol.1867 (6), p.130360-130360, Article 130360

2023

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Adapted tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methods

Scientific reports, 2022-10, Vol.12 (1), p.17438-20, Article 17438

2022

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A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

Scientific reports, 2022-12, Vol.12 (1), p.21242-21242, Article 21242

2022

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Relational patterns of gene expression via non-metric multidimensional scaling analysis

Bioinformatics, 2005-03, Vol.21 (6), p.730-740

2005

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Principal component analysis based feature extraction approach to identify circulating microRNA biomarkers

PloS one, 2013-06, Vol.8 (6), p.e66714-e66714

2013

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Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images

Scientific reports, 2024-11, Vol.14 (1), p.26520-17, Article 26520

2024

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Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Scientific reports, 2020-09, Vol.10 (1), p.15149-15149, Article 15149

2020

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Investigating the energy crisis in Alzheimer disease using transcriptome study

Scientific reports, 2019-12, Vol.9 (1), p.18509-13, Article 18509

2019

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Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction

PloS one, 2023-08, Vol.18 (8), p.e0289029-e0289029

2023

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A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

Gene, 2023-02, Vol.853, p.147038-147038, Article 147038

2023

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Machine learning algorithms for predicting drugs–tissues relationships

Expert systems with applications, 2019-08, Vol.127, p.167-186

2019

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Optimized Tensor Decomposition and Principal Component Analysis Outperforming State-of-the-Art Methods When Analyzing Histone Modification Chromatin Immunoprecipitation Profiles

Algorithms, 2023-09, Vol.16 (9), p.401

2023

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A new advanced in silico drug discovery method for novel coronavirus (SARS-CoV-2) with tensor decomposition-based unsupervised feature extraction

Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes

Drug candidate identification based on gene expression of treated cells using tensor decomposition-based unsupervised feature extraction for large-scale data

Tensor decomposition-based unsupervised feature extraction applied to matrix products for multi-view data processing

Features extracted using tensor decomposition reflect the biological features of the temporal patterns of human blood multimodal metabolome

Identification of genes associated with altered gene expression and m6A profiles during hypoxia using tensor decomposition based unsupervised feature extraction

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Unsupervised tensor decomposition-based method to extract candidate transcription factors as histone modification bookmarks in post-mitotic transcriptional reactivation

Bioinformatic tools for epitranscriptomics

Exploring microRNA Biomarker for Amyotrophic Lateral Sclerosis

Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more suitable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods

Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection tools

Tensor decomposition discriminates tissues using scATAC-seq

Adapted tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methods

A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

Relational patterns of gene expression via non-metric multidimensional scaling analysis

Principal component analysis based feature extraction approach to identify circulating microRNA biomarkers

Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Investigating the energy crisis in Alzheimer disease using transcriptome study

Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction

A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

Machine learning algorithms for predicting drugs–tissues relationships

Optimized Tensor Decomposition and Principal Component Analysis Outperforming State-of-the-Art Methods When Analyzing Histone Modification Chromatin Immunoprecipitation Profiles

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