Signalling network construction for modelling plant defence response.

Signalling network construction for modelling plant defence response.
复制标题

DOI:
10.1371/journal.pone.0051822
复制
发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Gruden K
Gruden K
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Miljkovic D;Stare T;Mozetič I;Podpečan V;Petek M;Witek K;Dermastia M;Lavrač N;Gruden K

文献摘要

参考文献

被引文献

相似文献

植物对包括病毒在内的各种病原体的防御信号应答是一种复杂的现象。在抗性相互作用中,植物细胞感知病原体信号,将其在细胞内转导并进行细胞代谢的重编程,导致病原体复制停滞。这项工作的重点是对植物防御反应至关重要的信号通路,即,水杨酸,茉莉酸和乙烯信号转导途径,在拟南芥模式植物。初始信令网络拓扑是通过定义表示形式、对公共数据库和文献中的信息进行编码以及绘制路径图来手动构建的。人工构建的网络结构由175个组分和387个反应组成。为了补充网络拓扑结构与可能丢失的关系,一种新的方法,从生物文献中自动提取信息。这种方法,名为Bio 3graph,允许从文献中自动提取生物关系,从而产生一组(component 1,反应,component 2)三元组,并组成一个图形结构,可以可视化,相比手动构建的拓扑结构,并由专家检查。使用植物防御反应的成分和反应类型词汇表,Bio 3graph应用于一组9,586篇相关的全文文章,导致137个新检测到的成分之间的反应。最后,将人工构建的拓扑结构和新反应合并,形成由175个组分和524个反应组成的网络结构。由此产生的植物防御信号通路图代表了一个有价值的来源,进一步的计算建模和组学数据的解释。开发的Bio 3graph方法,作为可执行的语言处理和图形可视化工作流,可在http://ropot.ijs.si/bio3graph/and上免费获得,如果提供足够的词汇表,可用于对其他生物系统进行建模。
Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for modelling other biological systems, given that an adequate vocabulary is provided.
DOI: 10.1186/1471-2105-5-147
发表时间: 2004-10-08
期刊: BMC bioinformatics
影响因子: 3
作者:
Chen H;Sharp BM
通讯作者: Sharp BM
DOI: 10.1109/mis.2002.999215
发表时间: 2002-03-01
影响因子: 6.4
作者:
Blaschke, C;Valencia, A
通讯作者: Valencia, A
DOI: 10.1371/journal.pcbi.0040020
发表时间: 2008-01
影响因子: 4.3
作者:
Cohen KB;Hunter L
通讯作者: Hunter L
DOI: 10.1093/bioinformatics/bth386
发表时间: 2004-11-22
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
Corney, DPA;Buxton, BF;Jones, DT
通讯作者: Jones, DT
DOI: 10.1162/coli.2006.32.4.485
发表时间: 2006-12-01
影响因子: 9.3
作者:
Kiss, Tibor;Strunk, Jan
通讯作者: Strunk, Jan