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Turki Turki

Professor

king abdulaziz university

Saudi Arabia

Research Interests

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Professors in Cell Biology

Articles (15)

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2026

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2026

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2026

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2025

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2025

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2023

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2023

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2023

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2023

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2023

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2023

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2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (1)

Y-h. Taguchi

Professor

Chuo University

JAPAN

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Turki Turki

Research Interests

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Articles (15)

Reduced Detection of Human Orphan Gene Transcripts in Disease Tissue Relative to Expression- and Detection- Matched Controls

Novel 4D Tensor Decomposition-Based Approach Integrating Tri-Omics Profiling Data Can Identify Functionally Relevant Gene Clusters

Automatic Bevacizumab Response Prediction in Ovarian Cancer from Digital Pathology Images via Novel AI-Based Computational Pipeline

Novel Tensor Decomposition-Based Approach for Cell-Type Deconvolution in Visium Datasets with Reference scRNA-Seq Data Containing Multiple Minor Cell Types

De Novo Single-Cell Biological Analysis of Drug Resistance in Human Melanoma Through a Novel Deep Learning-Powered Approach

GENEvaRX: A novel AI-driven method and web tool can identify critical genes and effective drugs for Lichen Planus

Integrated Analysis of Gene Expression and Protein–Protein Interaction with Tensor Decomposition

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

Tensor decomposition discriminates tissues using scATAC-seq

Tensor decomposition discriminates tissues using scATAC-seq

Applying Deep Transfer Learning to Assess the Impact of Imaging Modalities on Colon Cancer Detection

PDD-Net: Plant Disease Diagnoses Using Multilevel and Multiscale Convolutional Neural Network Features

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

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

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

Collaborators (1)

Y-h. Taguchi

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