1. 哈尔滨工业大学 计算机科学与技术学院,哈尔滨,150001
2. School of Computer Science and Technology, Harbin Institute of Technology,Harbin,150001
3. 北京建筑大学电气与信息工程学院,北京,100044
4. [KH-*1]
5. 建筑大数据智能处理方法研究北京市重点实验室,北京,100044
纸质出版:2018
移动端阅览
邢林林, 郭茂祖, 刘晓燕, 等. 水稻组织特异性蛋白质相互作用网络构建方法[J]. 哈尔滨工业大学学报, 2018,50(11):1-9.
XING Linlin, GUO Maozu, LIU Xiaoyan, et al. A tissue-specific protein interaction network construction method for rice[J]. 2018, 50(11): 1-9.
邢林林, 郭茂祖, 刘晓燕, 等. 水稻组织特异性蛋白质相互作用网络构建方法[J]. 哈尔滨工业大学学报, 2018,50(11):1-9. DOI: 10.11918/j.issn.0367-6234.201803117.
XING Linlin, GUO Maozu, LIU Xiaoyan, et al. A tissue-specific protein interaction network construction method for rice[J]. 2018, 50(11): 1-9. DOI: 10.11918/j.issn.0367-6234.201803117.
组织特异的基因表达和蛋白质相互作用是研究基因调控、蛋白质功能、细胞过程的重要部分.相较于其他模式生物在蛋白质相互作用研究方面的进展
高等模式植物水稻中组织特异性蛋白质相互作用的研究十分缺乏.因此
提出了一种用于水稻组织特异性蛋白质相互作用网络构建的计算方法.该方法主要包含三部分:第一
在统一标准下融合多数据识别组织特异的基因; 第二
提出了新的同源映射方法
并集成6种模式生物相互作用数据构建和评估目标物种蛋白质相互作用网络; 第三
构建不同组织的蛋白质相互作用子网
并筛选高可靠的蛋白质相互作用.为了验证方法的有效性
构建并分析了水稻首个组织特异的蛋白质相互作用网络(PTSN4R:Predicted Tissue-Specific Network for Rice).PTSN4R包含了水稻23个组织的组织特异基因及对应的组织特异蛋白质相互作用子网
为分析组织特异的基因表达和蛋白质相互作用提供了便利条件.PTSN4R有助于理解水稻的生长调控机制
为水稻增产提供线索.同时
提出的方法能够方便的应用到其他物种
促进组织特异的蛋白质相互作用网络的研究.
The expression pattern of genes and protein interactions in specific tissues are important frameworks for studying gene regulation
protein function
and cellular processes.Compared with the research progress of other model organisms in the interactome
the tissue-specific protein interaction research and development in higher plants is very slow
especially in rice.With this motivation
we have proposed a computing framework to predict tissue-specific protein-protein networks for rice.This framework consists of three parts:(a) identification of tissue-specific genes by integrating multiple dataset under a unified criterion; (b) prediction and evaluation of the protein interaction network based on the resource of six model organisms by using the proposed novel Interolog mapping method; (c) tissue-specific subnet construction in each tissue and high reliable interactions filter based on co-expression correlation.To evaluate the effectiveness of our framework
PTSN4R (Predicted Tissue-Specific Networks for Rice) is constructed and analyzed.PTSN4R is the first integrated database for tissue-specific protein interactions of rice
which contains tissue-specific genes and the interaction networks of 23 rice tissues.And
it provides a tissue-specific perspective to conveniently analyze the gene expression and protein interaction.These resources can help researchers understand the intrinsic regulatory mechanisms of rice growth and development and provide clues for rice yield increase.In addition
the proposed framework can extend to other species easily to improve the research of tissue-specific protein interactions.
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