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Journal of Nanobiotechnology|January 12, 2021
Decrease in membrane fluidity and traction force induced by silica-coated magnetic nanoparticlesTae Hwan Shin, Abdurazak Aman Ketebo, Da Yeon Lee, et al.
Journal of Molecular Recognition : JMR|April 8, 2011
Molecular modeling-based evaluation of dual function of IκBζ ankyrin repeat domain in toll-like receptor signalingBalachandran Manavalan, Rajivgandhi Govindaraj, Gwang Lee, et al.
Archives of Toxicology|February 10, 2019
Silica-coated magnetic nanoparticles induce glucose metabolic dysfunction in vitro via the generation of reactive oxygen speciesTae Hwan Shin, Chan Seo, Da Yeon Lee, et al.
Plos One|September 30, 2010
Molecular modeling-based evaluation of hTLR10 and identification of potential ligands in Toll-like receptor signalingRajiv Gandhi Govindaraj, Balachandran Manavalan, Gwang Lee, et al.
Computers in Biology and Medicine|February 27, 2023
Computational prediction of protein folding rate using structural parameters and network centrality measuresSaraswathy Nithiyanandam, Vinoth Kumar Sangaraju, Balachandran Manavalan, et al.
BMC Structural Biology|January 14, 2010
Molecular modeling of the reductase domain to elucidate the reaction mechanism of reduction of peptidyl thioester into its corresponding alcohol in non-ribosomal peptide synthetasesBalachandran Manavalan, Senthil K Murugapiran, Gwang Lee, et al.
Frontiers in Immunology|August 16, 2018
PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide PredictionsBalachandran Manavalan, Tae Hwan Shin, Myeong Ok Kim, et al.
Protein Science : a Publication of the Protein Society|July 10, 2026
SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptidesChan Woo Kwon, Minjun Kwon, Shaherin Basith, et al.
Frontiers in Pharmacology|April 12, 2018
AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random ForestBalachandran Manavalan, Tae H Shin, Myeong O Kim, et al.
Journal of Proteome Research|June 13, 2018
Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved AccuracyBalachandran Manavalan, Sathiyamoorthy Subramaniyam, Tae Hwan Shin, et al.
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