:

Guanghao Hu1, Jooa Moon1, Tomohiro Hayashi1,2

  • 1Department of Materials Science and Engineering, School of Materials Science and Chemical Technology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawa-ken 226-8502, Japan.

概括

这项研究预测了蛋白质的位置 (细胞质或分泌) 使用表面特征,如氨基酸群和二次结构. 一个随机的森林分类器实现了93.9%的准确性,揭示了蛋白质定位的关键特征.

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