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Briefings in Bioinformatics|December 7, 2023
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approachNhat Truong Pham, Le Thi Phan, Jimin Seo, et al.
IEEE Transactions on Computational Biology and Bioinformatics|August 14, 2025
TP-ML: A Machine-Learning-Based Tool to Identify Threonine Proteases Using Sequence-Derived Optimal FeaturesAhmad Firoz, Adeel Malik, Nitin Mahajan, et al.
Stem Cells International|August 29, 2018
Bidirectional Transcriptome Analysis of Rat Bone Marrow-Derived Mesenchymal Stem Cells and Activated Microglia in an In Vitro Coculture SystemDa Yeon Lee, Moon Suk Jin, Balachandran Manavalan, et al.
Stem Cells International|September 20, 2021
Strategies to Improve the Quality and Freshness of Human Bone Marrow-Derived Mesenchymal Stem Cells for Neurological DiseasesDa Yeon Lee, Sung Eun Lee, Do Hyeon Kwon, et al.
Nanomaterials (Basel, Switzerland)|September 28, 2021
Analysis of Nanotoxicity with Integrated Omics and MechanobiologyTae Hwan Shin, Saraswathy Nithiyanandam, Da Yeon Lee, et al.
Journal of Chemical Information and Modeling|March 14, 2025
Employing Automated Machine Learning (AutoML) Methods to Facilitate the In Silico ADMET Properties PredictionHerim Han, Bilal Shaker, Jin Hee Lee, et al.
Pharmaceutics|May 27, 2026
Integrative Peptide Drug Development: Chemical Engineering, AI-Driven Design, and Cell-Penetrating PeptidesYong Eun Jang, Minjun Kwon, Chan Woo Kwon, et al.
Molecular Therapy : the Journal of the American Society of Gene Therapy|May 8, 2022
Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategyMd Mehedi Hasan, Sho Tsukiyama, Jae Youl Cho, et al.
Computers in Biology and Medicine|June 2, 2023
Identification of SH2 domain-containing proteins and motifs prediction by a deep learning methodDuanzhi Wu, Xin Fang, Kai Luan, et al.
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