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DESCRIPTION (provided by applicant): Biochemical networks are meshes of homologous and non-homologous proteins. The "small world" topology - often scale free and in which a small number of hub nodes display extraordinarily high connectivity - is detected in the network models generated from omics results. Genomic basis of the scale-free topology - how to deduce this topology from genomic sequences - remains an open question. This proposal initiates an attempt to find a footing for this topology in genomic sequences. The focus is functional diversification of paralogous proteins and the formation of parallel pathways in the networks, in which the intrinsically disordered protein (IDP) segments is hypothesized to play preeminent roles. Our specific aims are as follows. 1: Quantifying parallel pathways in biochemical networks. Our preliminary studies suggest paralogous proteins diverge in their functional specificity to form parallel pathways. The proteome sequences would be clustered into families and each protein assigned to a numerical family ID. Biochemical network models would then be annotated with this numerical format. Subsequently, parallel pathways can be visualized and quantified by analysis combinatorial patterns of these numerical IDs. 2: Roles of disordered regions in the topology of biochemical networks. It is hypothesized that IDPs are crucial for functional diversification of paralogous proteins. This hypothesis will be tested by a combination of genome wide IDP analysis, comparative genomic analysis as well as experimental verification. 3: Scale-free distribution and multi-cellularity. The exponent constant in power-law distribution varies across species. This constant would be determined for specific tissue/cell types in order to explain this variation from single cell species to multi-cellular species. The roles of disordered regions in functional diversification of paralogous proteins in multi-cellular species would also be investigated.
期刊论文(6)
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Tyrosine phosphorylation regulates ERβ ubiquitination, protein turnover, and inhibition of breast cancer.
酪氨酸磷酸化调节 ER β 泛素化、蛋白质周转和乳腺癌抑制
DOI: 10.18632/oncotarget.10018
发表时间: 2016-07-05
期刊: Oncotarget
影响因子: --
作者: [Yuan B, Cheng L, Gupta K, Chiang HC, Gupta HB, Sareddy GR, Wang D, Lathrop K, Elledge R, Wang P, McHardy S, Vadlamudi R, Curiel TJ, Hu Y, Ye Q, Li R]
通讯作者: Li R
DOI: 10.1093/nar/gks464
发表时间: 2012-09
期刊: Nucleic acids research
影响因子: 14.9
作者: [Padawer T, Leighty RE, Wang D]
通讯作者: Wang D
DOI: 10.1038/s41598-018-24039-1
发表时间: 2018-04-10
期刊: Scientific reports
影响因子: 4.6
作者: [Jiang W, Guo Z, Lages N, Zheng WJ, Feliers D, Zhang F, Wang D]
通讯作者: Wang D
DOI: 10.3390/genes8110296
发表时间: 2017-10-27
期刊: Genes
影响因子: 3.5
作者: [Zhang F, Wang D]
通讯作者: Wang D
Regulation of anti-tumor immunity by HDAC11
  • 批准号:
    10436938
  • 项目类别:
  • 资助金额:
    $56.97万
  • 财政年份:
    2020
  • 负责人:
    Rong Li
  • 依托单位:
Regulation of anti-tumor immunity by HDAC11
  • 批准号:
    10524141
  • 项目类别:
  • 资助金额:
    $8.44万
  • 财政年份:
    2020
  • 负责人:
    Rong Li
  • 依托单位:
Regulation of anti-tumor immunity by HDAC11
  • 批准号:
    10640210
  • 项目类别:
  • 资助金额:
    $56.14万
  • 财政年份:
    2020
  • 负责人:
    Rong Li
  • 依托单位:
Boosting Antitumor Immunity by Blocking Both Tumor and Adipose DDR1
  • 批准号:
    9980667
  • 项目类别:
  • 资助金额:
    $47.69万
  • 财政年份:
    2020
  • 负责人:
    Rong Li
  • 依托单位:
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