Browsing "Physiology" by Keyword : Machine learning
Showing results 4 to 13 of 13
Pub Year | | Title | Author(s) |
2020 | | i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes | Balachandran, Manavalan |
2020 | | i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome | Balachandran, Manavalan |
2020 | | i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation | Balachandran, Manavalan |
2018 | | iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
2022 | | Recent Trends on the Development of Machine Learning Approaches for the Prediction of Lysine Acetylation Sites | Basith, Shaherin, 이광, 장혜진 |
2024 | | Reduced lysosomal activity and increased amyloid beta accumulation in silica-coated magnetic nanoparticles-treated microglia | 이광 |
2022 | | SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids | Balachandran, Manavalan |
2021 | | Silica-coated magnetic-nanoparticle-induced cytotoxicity is reduced in microglia by glutathione and citrate identified using integrated omics | Balachandran, Manavalan, Basith, Shaherin, 강엽, 김아영, 백은주, 신태환, 이광 |
2021 | | SortPred: The first machine learning based predictor to identify bacterial sortases and their classes using sequence-derived information | Balachandran, Manavalan |
2021 | | Umpred-frl: A new approach for accurate prediction of umami peptides using feature representation learning | Balachandran, Manavalan |
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