Schizophrenia genes: characteristics of function and protein interaction networks

被引:1
|
作者
Sun, Jingchun [1 ]
Han, Leng [2 ]
Zhao, Zhongming [1 ]
机构
[1] Virginia Commonwealth Univ, Ctr Study Biol Complex, Dept Psychiat, Richmond, VA 23284 USA
[2] Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming, Peoples R China
关键词
D O I
10.1109/BMEI.2008.227
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Schizophrenia is a heritable complex disease that involves multiple genes interacting themselves or with environment. Its genetic mechanisms have not been well understood. Currently, studies have revealed hundreds of genes associated with schizophrenia. This provides us an opportunity to explore the molecular characteristics of schizophrenia genes (SCZGenes) using genomics and systems biology approaches. In this study, we selected SCZGenes based on the published association studies and examined their functional features by comparing to the neurodevelopmental genes and control genes. We revealed that SCZGenes have strong correlation with neurodevelopment and other functional term. We further investigated the topological characteristics of SCZGenes in the human protein interaction network. We found that SCZGenes do not tend to encode hub proteins; rather they interact in a modest degree. Finally, we extracted SCZGenes subnetworks, which may be further analyzed with other information.
引用
收藏
页码:437 / +
页数:2
相关论文
共 50 条
  • [41] Predicting Protein Function by Frequent Functional Association Pattern Mining in Protein Interaction Networks
    Cho, Young-Rae
    Zhang, Aidong
    IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2010, 14 (01): : 30 - 36
  • [42] IDENTIFICATION OF FUNCTION MODULES IN PROTEIN-PROTEIN INTERACTION NETWORKS BY MODULARITY OPTIMIZATION METHOD
    Feng, Jun
    Jia, Ning-Ning
    Qi, Zhao-Hui
    Zhang, Xiao-Fen
    PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL. 1, 2015, : 47 - 51
  • [43] Integrating omics data and protein interaction networks to prioritize driver genes in cancer
    Zhang, Tiejun
    Zhang, Di
    ONCOTARGET, 2017, 8 (35) : 58050 - 58060
  • [44] Construction of HBV-HCC prognostic model and immune characteristics based on potential genes mining through protein interaction networks
    Li, Qingxiu
    Wu, Kejia
    Zhang, Yiqi
    Liu, Yuxin
    Wang, Yalan
    Chen, Yong
    Sun, Shuangling
    Duan, Changzhu
    JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2023, 149 (13) : 11263 - 11278
  • [45] Construction of HBV-HCC prognostic model and immune characteristics based on potential genes mining through protein interaction networks
    Qingxiu Li
    Kejia Wu
    Yiqi Zhang
    Yuxin Liu
    Yalan Wang
    Yong Chen
    Shuangling Sun
    Changzhu Duan
    Journal of Cancer Research and Clinical Oncology, 2023, 149 : 11263 - 11278
  • [46] Exploring Function Prediction in Protein Interaction Networks via Clustering Methods
    Trivodaliev, Kire
    Bogojeska, Aleksandra
    Kocarev, Ljupco
    PLOS ONE, 2014, 9 (06):
  • [47] Protein function prediction using guilty by association from interaction networks
    Damiano Piovesan
    Manuel Giollo
    Carlo Ferrari
    Silvio C. E. Tosatto
    Amino Acids, 2015, 47 : 2583 - 2592
  • [48] Protein function prediction using guilty by association from interaction networks
    Piovesan, Damiano
    Giollo, Manuel
    Ferrari, Carlo
    Tosatto, Silvio C. E.
    AMINO ACIDS, 2015, 47 (12) : 2583 - 2592
  • [49] Protein interaction networks in neurodegenerative diseases: From physiological function to aggregation
    Calabrese, Gaetano
    Molzahn, Cristen
    Mayor, Thibault
    JOURNAL OF BIOLOGICAL CHEMISTRY, 2022, 298 (07)
  • [50] The impact of protein interaction networks' characteristics on computational complex detection methods
    Liu, Xiaoxia
    Yang, Zhihao
    Zhou, Ziwei
    Sun, Yuanyuan
    Lin, Hongfei
    Wang, Jian
    Xu, Bo
    JOURNAL OF THEORETICAL BIOLOGY, 2018, 439 : 141 - 151