Network-assisted protein identification and data interpretation in shotgun proteomics.
Network-assisted protein identification and data interpretation in shotgun proteomics.
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DOI：
10.1038/msb.2009.54
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发表时间：
2009
影响因子：
9.9
通讯作者：
Zhang, Bing
中科院分区：
文献类型：
--
作者：
Li, Jing;Zimmerman, Lisa J.;Park, Byung-Hoon;Tabb, David L.;Liebler, Daniel C.;Zhang, Bing
蛋白质组装和组装蛋白质序列的生物学解释是鸟枪法蛋白质组学数据分析的关键步骤。虽然大多数生物功能来自蛋白质之间的相互作用，但目前的蛋白质组装管道将蛋白质视为独立实体。通常情况下，只有个别蛋白质与强有力的实验证据，即有信心的蛋白质，而许多可能的蛋白质的生物学利益被排除。我们已经开发了一种case-enrichment方法（CEA），通过将蛋白质之间的关系嵌入到蛋白质相互作用网络中来拯救被消除的蛋白质。在测试的几个数据集中，CEA使蛋白质鉴定提高了8-23%，估计准确率为85%。现有文献或转录组分析研究支持挽救的蛋白质与置信蛋白质的水平相似，并且比废弃蛋白质的水平显著更高。将CEA应用于乳腺癌数据集，拯救了由众所周知的乳腺癌基因编码的蛋白质。此外，CEA生成了蛋白质的网络视图，并有助于显示可能支持疾病分子机制的蛋白质的模块化组织。
Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique-enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8–23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well-known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease.
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影响因子：
12.3
作者：
Hart GT;Ramani AK;Marcotte EM
通讯作者：
Marcotte EM
影响因子：
64.8
作者：
Jeong, H;Mason, SP;Oltvai, ZN
通讯作者：
Oltvai, ZN
影响因子：
64.8
作者：
Gavin, AC;Aloy, P;Superti-Furga, G
通讯作者：
Superti-Furga, G
DOI：
10.1073/pnas.0307326101
发表时间：
2004-03-02
影响因子：
11.1
作者：
Karaoz, U;Murali, TM;Kasif, S
通讯作者：
Kasif, S
影响因子：
64.5
作者：
Foster, LJ;de Hoog, CL;Mann, M
通讯作者：
Mann, M