蛋白质复合体对于研究细胞活动具有重要意义.随着新的生物实验技术的不断出现,产生了大量的蛋白质相互作用网络.通过对蛋白质相互作用网络进行聚类识别蛋白质复合体是当前研究热点.然而,目前大多数蛋白质复合体识别算法的性能不够理想....蛋白质复合体对于研究细胞活动具有重要意义.随着新的生物实验技术的不断出现,产生了大量的蛋白质相互作用网络.通过对蛋白质相互作用网络进行聚类识别蛋白质复合体是当前研究热点.然而,目前大多数蛋白质复合体识别算法的性能不够理想.为此,提出了蛋白质复合体模块度函数(PQ),并在此基础上提出了基于蛋白质复合体模块度函数的模块合并(based on protein complexes modularity function for merging modules,BMM)算法.BMM算法首先识别网络中一些稠密子图作为初始模块,然后依据PQ函数对这些初始模块进行合并,最终得到了质量较高的蛋白质复合体.将识别出的复合体分别与2种已知的蛋白质复合体数据集进行比对,结果表明BMM算法具有很好的识别性能.此外,与其他最新的识别算法相比,BMM算法的识别准确率较高.展开更多
Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high...Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.展开更多
文摘蛋白质复合体对于研究细胞活动具有重要意义.随着新的生物实验技术的不断出现,产生了大量的蛋白质相互作用网络.通过对蛋白质相互作用网络进行聚类识别蛋白质复合体是当前研究热点.然而,目前大多数蛋白质复合体识别算法的性能不够理想.为此,提出了蛋白质复合体模块度函数(PQ),并在此基础上提出了基于蛋白质复合体模块度函数的模块合并(based on protein complexes modularity function for merging modules,BMM)算法.BMM算法首先识别网络中一些稠密子图作为初始模块,然后依据PQ函数对这些初始模块进行合并,最终得到了质量较高的蛋白质复合体.将识别出的复合体分别与2种已知的蛋白质复合体数据集进行比对,结果表明BMM算法具有很好的识别性能.此外,与其他最新的识别算法相比,BMM算法的识别准确率较高.
基金Project supported by the National Scientific Research Foundation of Hunan Province, China （Nos. 14C0096, 10C0408, and 10B010）, the Natural Science Foundation of Hunan Province, China （Nos. 13JJ4106 and 14J J3138）, and the Science and Technology Plan Project of Hunan Province, China （No. 2010FJ3044）
文摘Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.
