摘要
Alpha-synuclein plays an important role in Parkinson's disease(PD).The current study of alpha-synuclein mainly concentrates at the gene level.However, it is found that the study at the protein level has special significance.Meanwhile, there is free information on the Internet, such as databases and algorithms of protein-protein interactions(PPIs).In this paper, a novel method which integrates distributed heterogeneous data sources and algorithms to predict PPIs for alpha-synuclein in silico is proposed.The PPIs generated by the method take advantage of various experimental data, and indicate new information about PPIs for alpha-synuclein.In the end of this paper, the result illustrates that the method is practical.It is hoped that the prediction result obtained by this method can provide guidance for biological experiments of PPIs for alpha-synuclein to reveal possible mechanisms of PD.
Alpha-synuclein plays an important role in Parkinson＇s disease （PD）. The current study of alpha-synuclein mainly concentrates at the gene level. However, it is found that the study at the protein level has special significance. Meanwhile, there is free information on the Internet, such as databases and algorithms of protein-protein interactions （PPIs）. In this paper, a novel method which integrates distributed heterogeneous data sources and algorithms to predict PPIs for alpha- synuclein in silico is proposed. The PPIs generated by the method take advantage of various experimental data, and indicate new information about PPIs for alpha-synuclein. In the end of this paper, the result illustrates that the method is practical. It is hoped that the prediction result obtained by this method can provide guidance for biological experiments of PPIs for alpha-synuclein to reveal possible mechanisms of PD.
基金
supported by the National Basic Research Program of China (Grant No.2006CB500702)
the Shanghai Lead-ing Academic Discipline Project (Grant No.J50103)
Shanghai University Systems Biology Reasearch Funding (GrantNo.SBR08001)
