细胞外基质蛋白质预测工具研究进展

Advances in the research of extracellular matrix protein prediction tools

细胞外基质蛋白质在细胞的一系列生物过程中发挥着重要作用,它的异常调节会导致很多重大疾病。理论细胞外基质蛋白质参考数据是实现细胞外基质蛋白质高效鉴定的基础,研究者们已经基于机器学习的方法开发出一系列的细胞外基质蛋白质预测工具。文中首先阐述了基于机器学习模型构建细胞外基质蛋白质预测工具的基本流程,之后以工具为单位总结了已有细胞外基质蛋白质预测工具的研究成果,最后提出了细胞外基质蛋白质预测工具目前面临的问题和可能的优化方法。

Extracellular matrix(ECM)proteins play an important role in a series of biological processes in the cell,and their abnormal regulation can lead to many diseases.The theoretical ECM reference dataset is the basis for efficient identification of extracellular matrix proteins.Researchers have developed various ECM protein prediction tools based on machine learning methods.In this review,the main strategy of development of ECM protein prediction tools that based on machine learning methods has been introduced.Then,advances and specific characters of the existing ECM protein prediction tools have been summarized.Finally,the challenges and possible improvements of ECM protein prediction tools are discussed.