Suppr超能文献

蛋白质-蛋白质相互作用:通过图论建模理解网络。

Protein-protein interactions: making sense of networks via graph-theoretic modeling.

机构信息

Department of Computing, Imperial College London, London, UK.

出版信息

Bioessays. 2011 Feb;33(2):115-23. doi: 10.1002/bies.201000044.

Abstract

The emerging area of network biology is seeking to provide insights into organizational principles of life. However, despite significant collaborative efforts, there is still typically a weak link between biological and computational scientists and a lack of understanding of the research issues across the disciplines. This results in the use of simple computational techniques of limited potential that are incapable of explaining these complex data. Hence, the danger is that the community might begin to view the topological properties of network data as mere statistics, rather than rich sources of biological information. A further danger is that such views might result in the imposition of scientific doctrines, such as scale-free-centric (on the modeling side) and genome-centric (on the biological side) opinions onto this area. Here, we take a graph-theoretic perspective on protein-protein interaction networks and present a high-level overview of the area, commenting on possible challenges ahead.

摘要

网络生物学这一新兴领域旨在深入了解生命的组织原则。然而,尽管合作努力显著,但生物学家和计算机科学家之间通常存在薄弱环节,并且对跨学科的研究问题缺乏了解。这导致了简单计算技术的使用,这些技术的潜力有限,无法解释这些复杂的数据。因此,危险在于该领域可能开始将网络数据的拓扑性质仅仅视为统计数据,而不是丰富的生物学信息来源。另一个危险是,这种观点可能会导致科学学说的强加,例如无标度中心(在建模方面)和基因组中心(在生物学方面)观点强加于该领域。在这里,我们从图论的角度来看待蛋白质-蛋白质相互作用网络,并对该领域进行了高级概述,评论了未来可能面临的挑战。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验