We then used a machine learning approach to deduce a protein interaction map that is most consistent with the underlying domain information. 为此我们对蛋白质序列进行了结构域的划分和映射,并采用机器学习的方法提取出结构域之间的相互作用。
We convert protein sequences of interaction network into the corresponding discrete vector by pseudo amino acid composition method, and then use classification model to predict them, finally draw the map for the prediction results of protein interaction networks. 我们分别对两种相互作用网络中所有的蛋白质序列利用伪氨基酸组成方法转换成相应的离散化向量,然后再利用分类器模型进行预测,最后对预测的结果绘制了蛋白质相互作用网络图谱。