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语境特异蛋白网络挖掘器——一个在线系统,用于从文献中挖掘语境特异蛋白相互作用网络。

Context-specific protein network miner--an online system for exploring context-specific protein interaction networks from the literature.

机构信息

Marshfield Clinic Research Foundation-Biomedical Informatics Research Center, Marshfield, Wisconsin, United States of America.

出版信息

PLoS One. 2012;7(4):e34480. doi: 10.1371/journal.pone.0034480. Epub 2012 Apr 6.

Abstract

BACKGROUND

Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis.

RESULTS

We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality.

CONCLUSIONS

CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/.

摘要

背景

特定于特定上下文的蛋白质相互作用网络 (PINs) 包含许多细胞生物学过程的关键信息。例如,PINs 可能包括关于相互作用的类型和方向性(例如磷酸化)、相互作用的位置(即组织、细胞)以及相关疾病的信息。目前,很少有工具能够针对进行探索性分析的特定于上下文的 PINs 进行推导。

结果

我们开发了一个基于文献的在线系统,即特定于上下文的蛋白质网络挖掘器 (CPNM),它可以根据用户输入的一组关键字和增强的 PubMed 查询系统,实时从 PubMed 数据库中推导出特定于上下文的 PINs。CPNM 报告了有关蛋白质相互作用的丰富信息(包括类型和方向性),以及其网络拓扑结构的汇总统计信息(例如网络中最密集连接的蛋白质;最密集连接的蛋白质对;以及通过最多入站/出站链接连接的蛋白质),这些信息可以通过用户友好的界面进行探索。CPNM 系统的一些新颖功能包括 PIN 生成、基于本体论的 PubMed 查询增强、实时、用户查询、最新的 PubMed 文档处理以及 PIN 方向性的预测。

结论

CPNM 为生物学家提供了一种探索 PINs 的工具。它可以免费在 http://www.biotextminer.com/CPNM/ 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bbb/3321019/f71841aed76e/pone.0034480.g001.jpg

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