Abstract
RNA pseudouridine modification exists in different RNA types of many species, and it has a significant role in regulating the expression of biological processes. To understand the functional mechanisms for RNA pseudouridine sites, accurate identification of pseudouridine sites in RNA sequences is essential. Although several fast and inexpensive computational methods have been proposed, the challenge of improving recognition accuracy and generalization is still existing. This study proposed a novel ensemble predictor called PsoStack-PseU for improved RNA pseudouridine sites prediction. After analyzing the nucleotide composition preferences between RNA pseudouridine site sequences, two feature representations were determined and fed into the stacking ensemble framework. Then using five tree-based machine learning classifiers as base-classifiers construct 30-dimensional RNA profiles to represent RNA sequences, and using the PSO algorithm searches the weights of RNA profiles to further enhance the representation. A Logistic Regression classifier was used as a meta-classifier to complete the final predictions. Compared to the most advanced predictors, the performance of PsoStack-PseU is superior on both cross-validation and the independent test. Based on the PsoStack-PseU predictor, a free and easy-to-operate web server has been established, which will be a powerful tool for pseudouridine site identification.
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Funding
This work was supported in part by funds from the Key Research Project of Colleges and Universities of Henan Province (No.22A520013, No. 23B520004), the Key Science and Technology Development Program of Henan Province (No. 232102210020, No. 202102210144), the Training Program of Young Backbone Teachers in Colleges and Universities of Henan Province (No. 2019GGJS132).
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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Wang, X., Li, P., Han, L., Wang, R. (2023). A Stacking-Based Ensemble Learning Predictor Combined with Particle Swarm Optimizer for Identifying RNA Pseudouridine Sites. In: Huang, DS., Premaratne, P., Jin, B., Qu, B., Jo, KH., Hussain, A. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2023. Lecture Notes in Computer Science, vol 14088. Springer, Singapore. https://doi.org/10.1007/978-981-99-4749-2_44
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DOI: https://doi.org/10.1007/978-981-99-4749-2_44
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