Department of Bioinformatics, Asia University, 500 Lioufeng Road, Wufeng Shiang, Taichung, Taiwan.
Comput Biol Med. 2010 Mar;40(3):300-5. doi: 10.1016/j.compbiomed.2010.01.001. Epub 2010 Jan 20.
A protein function pair approach, based on protein-protein interaction (PPI) data, is proposed to predict protein functions. Randomization tests are performed on the PPI dataset, which resulted in a protein function correlation scoring value which is used to rank the relative importance of a function pair. It has been found that certain classes of protein functions tend to be correlated together. Scoring values of these correlation pairs allow us to predict the functionality of a protein given that it interacts with proteins having well-defined function annotations. The jackknife test is used to validate the function pair method. The protein function pair approach achieves a prediction sensitivity comparable to an approach using more sophisticated method. The main advantages of this approach are as follows: (i) a set of function-function correlation relations are derived and intuitive biological interpretation can be achieved, and (ii) its simplicity, only two parameters are needed.
提出了一种基于蛋白质-蛋白质相互作用（PPI）数据的蛋白质功能对预测方法。对 PPI 数据集进行了随机化检验，得到了蛋白质功能相关性评分值，用于对功能对的相对重要性进行排序。研究发现，某些类别的蛋白质功能往往相互关联。这些相关对的评分值使我们能够预测给定蛋白质的功能，只要它与具有明确定义功能注释的蛋白质相互作用。采用jackknife 检验对功能对方法进行验证。蛋白质功能对方法的预测灵敏度可与使用更复杂方法的方法相媲美。该方法的主要优点如下：（i）推导了一组功能-功能相关关系，并可进行直观的生物学解释，以及（ii）其简单性，仅需要两个参数。
