Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology

doi:10.1093/nar/gkn257

南華大學機構典藏系統 > 科技學院 > 資訊工程學系 > 期刊論文 > Item 987654321/26810

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题名:	Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology
作者:	金家豪;Chin, Chia-Hao;Lin, Chung-Yen;Wu, Hsin-Hung;Chen, Shu-Hwa;Ho, Chin-Wen;Ko, Ming-Tat
貢獻者:	資訊工程學系
日期:	2008-07
上传时间:	2019-03-06 15:19:11 (UTC+8)
摘要:	One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small-or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC \|\| MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y₂H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human.
關聯:	Nucleic Acids Research vol. 36 sup. 2 pp.438-443
显示于类别:	[Department of Computer Science and Information Engineering] Periodical Articles

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档案	描述	大小	格式	浏览次数
Hubba hub.pdf		3815Kb	Adobe PDF	549	检视/开启

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