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Turki Turki

Showing results (21-30 of 36) with videos related to

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BMC Bioinformatics|December 19, 2024
Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interactionY-H Taguchi, Turki Turki
Frontiers in Artificial Intelligence|September 18, 2023
Application note: TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extractionY-H Taguchi, Turki Turki
Plos One|September 29, 2022
Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection toolsY-H Taguchi, Turki Turki
Scientific Reports|October 19, 2022
Adapted tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methodsY-H Taguchi, Turki Turki
Frontiers in Genetics|October 15, 2019
Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression AnalysisY-H Taguchi, Turki Turki
Genes|June 24, 2022
Integrated Analysis of Tissue-Specific Gene Expression in Diabetes by Tensor Decomposition Can Identify Possible Associated DiseasesY-H Taguchi, Turki Turki
Polymers|December 10, 2021
Effects of Collagen-Glycosaminoglycan Mesh on Gene Expression as Determined by Using Principal Component Analysis-Based Unsupervised Feature ExtractionY-H Taguchi, Turki Turki
IEEE Journal of Selected Topics in Signal Processing|November 23, 2021
Application of Tensor Decomposition to Gene Expression of Infection of Mouse Hepatitis Virus Can Identify Critical Human Genes and Efffective Drugs for SARS-CoV-2 InfectionY-H Taguchi, Turki Turki
Genes|December 16, 2020
Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics DataY-H Taguchi, Turki Turki
Genomics|February 22, 2023
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 methodsY-H Taguchi, Turki Turki
Pageof 4

Showing results (21-30 of 36) with videos related to

Sort By:
Pageof 4
BMC Bioinformatics|December 19, 2024
Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interactionY-H Taguchi, Turki Turki
Frontiers in Artificial Intelligence|September 18, 2023
Application note: TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extractionY-H Taguchi, Turki Turki
Plos One|September 29, 2022
Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection toolsY-H Taguchi, Turki Turki
Scientific Reports|October 19, 2022
Adapted tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methodsY-H Taguchi, Turki Turki
Frontiers in Genetics|October 15, 2019
Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression AnalysisY-H Taguchi, Turki Turki
Genes|June 24, 2022
Integrated Analysis of Tissue-Specific Gene Expression in Diabetes by Tensor Decomposition Can Identify Possible Associated DiseasesY-H Taguchi, Turki Turki
Polymers|December 10, 2021
Effects of Collagen-Glycosaminoglycan Mesh on Gene Expression as Determined by Using Principal Component Analysis-Based Unsupervised Feature ExtractionY-H Taguchi, Turki Turki
IEEE Journal of Selected Topics in Signal Processing|November 23, 2021
Application of Tensor Decomposition to Gene Expression of Infection of Mouse Hepatitis Virus Can Identify Critical Human Genes and Efffective Drugs for SARS-CoV-2 InfectionY-H Taguchi, Turki Turki
Genes|December 16, 2020
Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics DataY-H Taguchi, Turki Turki
Genomics|February 22, 2023
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 methodsY-H Taguchi, Turki Turki
Pageof 4