蛋白质亚细胞定位预测及相关主题的最新进展
Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics.
作者信息
Nakai Kenta, Wei Leyi
机构信息
Institute of Medical Science, The University of Tokyo, Minato-Ku, Japan.
School of Software, Shandong University, Jinan, China.
出版信息
Front Bioinform. 2022 May 19;2:910531. doi: 10.3389/fbinf.2022.910531. eCollection 2022.
Abstract
Prediction of subcellular localization of proteins from their amino acid sequences has a long history in bioinformatics and is still actively developing, incorporating the latest advances in machine learning and proteomics. Notably, deep learning-based methods for natural language processing have made great contributions. Here, we review recent advances in the field as well as its related fields, such as subcellular proteomics and the prediction/recognition of subcellular localization from image data.
摘要
从氨基酸序列预测蛋白质的亚细胞定位在生物信息学领域有着悠久的历史，并且仍在积极发展，融入了机器学习和蛋白质组学的最新进展。值得注意的是，基于深度学习的自然语言处理方法做出了巨大贡献。在这里，我们回顾该领域及其相关领域的最新进展，如亚细胞蛋白质组学以及从图像数据预测/识别亚细胞定位。
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