On the prediction of DNA-binding proteins only from primary sequences: A deep learning approach论文笔记
Abstract DNA结合蛋白在真核和原核蛋白质组的选择性剪接，RNA编辑，甲基化和许多其他生物学功能中发挥关键作用。从一级氨基酸序列预测这些蛋白质的功能正成为基因组功能注释的主要挑战之一。传统的预测方法通常致力于从序列中提取生理化学特征，但忽略图案之间的基序信息和位置信息。同时，训练数据中的小规模数据量和大噪声导致预测的准确性和可靠性较低。在本文中，我们提出了一种基于深度学习的方
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