ProJect: a powerful mixed-model missing value imputation method

• Main Authors: Kong, Weijia, Wong, Bertrand Jern Han, Hui, Harvard Wai Hann, Lim, Kai-Peng, Wang, Yulan, Wong, Limsoon, Goh, Wilson Wen Bin
• 其他作者: School of Biological Sciences
• 格式: Article
• 語言: English
• 出版: 2023
• 主題: Science::Biological sciences; Bioinformatics; Missing at Random
• 在線閱讀: https://hdl.handle.net/10356/171093
• 機構: Nanyang Technological University

Missing values (MVs) can adversely impact data analysis and machine-learning model development. We propose a novel mixed-model method for missing value imputation (MVI). This method, ProJect (short for Protein inJection), is a powerful and meaningful improvement over existing MVI methods such as Bay...