Deep Learning-Based Identification of Rab Proteins: A Convolutional Neural Network Approach with Evolutionary Information Integration
學年 114
學期 1
發表日期 2025-09-12
作品名稱 Deep Learning-Based Identification of Rab Proteins: A Convolutional Neural Network Approach with Evolutionary Information Integration
作品名稱（其他語言）
著者 Le Nguyen Quoc Khanh; Nguyen Van-Nui; Nguyen Thi-Tuyen; Tran Thi-Xuan; Ho Trang-Thi; Ho Van-Lam
作品所屬單位
出版者
會議名稱 the 2024 International Conference on Intelligence of Things(ICIT 2024)
會議地點 Danang, Viet Nam
摘要 Rab proteins play a crucial role in membrane trafficking and are implicated in various human diseases. Accurate identification of Rab proteins within membrane proteins is of utmost importance for comprehending these diseases and establishing effective drug targets. In this study, we applied a two-dimensional convolutional neural network (CNN) integrated with evolutionary information to discern and identify Rab proteins present within general proteins. Our CNN model exhibited notable performance, achieving a sensitivity of 93.3%, specificity of 98%, accuracy of 96.9%, and a Matthews correlation coefficient (MCC) of 0.91 when tested on an independent dataset. In comparison to previously published methodologies, our approach displayed a substantial 25% improvement in the identification of Rab GTPases. These findings underscore the potential of deep learning techniques for accurately discerning Rab proteins and lay the groundwork for future investigations employing deep learning in the field of bioinformatics.
關鍵字
語言 en
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會議性質 國內
校內研討會地點 無
研討會時間 20250912~20250914
通訊作者
國別 TWN
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相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/129061 )