根据蛋白质互作网络预测乳腺癌相关蛋白质的细致功能

乳腺癌是最为常见的恶性肿瘤之一。已有的关于乳腺癌相关蛋白质的功能注释比较宽泛, 制约了乳腺癌的后续研究工作。对于已知部分功能的乳腺癌相关蛋白质, 提出了一种结合Gene Ontology功能先验知识和蛋白质互作的方法, 通过构建功能特异的局部相互作用网络来预测乳腺癌相关蛋白质的细致功能。结果显示该方法能够以很高的精确率为乳腺癌相关蛋白质预测更为精细的功能。预测的相关蛋白质的功能对于指导实验研究乳腺癌的分子机制具有重要的价值。

Finding finer functions for proteins related to breast cancer based on protein interaction network

Breast cancer is one of the most common malignant tumours. However, the existing functional knowledge about the proteins related to the breast cancer is too general to promote the following study. To find their finer functions, we suggest using the function-specific interaction sub-networks by integrating the functional knowledge of Gene Ontology and the protein-protein interaction network. The results show that the proposed approach is able to reliably find finer functions for these proteins with high precision. The predicted finer functions are highly valuable for guiding the follow-up wet-lab research to study the molecular mechanism of breast cancer.