Sharma Pooja, Bhattacharyya Dhruba K, Kalita Jugal K
Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam 784 028, India.
J Biosci. 2017 Sep;42(3):383-396. doi: 10.1007/s12038-017-9696-3.
Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexes from raw protein-protein interactions (PPIs) is an important area of research. Earlier work has been limited mostly to yeast and a few other model organisms. Such protein complex identification methods, when applied to large human PPIs often give poor performance. We introduce a novel method called ComFiR to detect such protein complexes and further rank diseased complexes based on a query disease. We have shown that it has better performance in identifying protein complexes from human PPI data. This method is evaluated in terms of positive predictive value, sensitivity and accuracy. We have introduced a ranking approach and showed its application on Alzheimer's disease.
众所周知，蛋白质复合物在控制生物体内的细胞活动中起着主要作用。从原始蛋白质-蛋白质相互作用（PPI）中识别复合物是一个重要的研究领域。早期的工作大多局限于酵母和其他一些模式生物。当将此类蛋白质复合物识别方法应用于大型人类PPI时，其性能往往较差。我们引入了一种名为ComFiR的新方法来检测此类蛋白质复合物，并根据查询疾病对患病复合物进行进一步排名。我们已经表明，该方法在从人类PPI数据中识别蛋白质复合物方面具有更好的性能。该方法根据阳性预测值、敏感性和准确性进行评估。我们引入了一种排名方法，并展示了其在阿尔茨海默病中的应用。
