FunCoup 6:通过定向链接推进跨物种功能关联网络并改善用户体验

Davide Buzzao, Emma Persson, Dimitri Guala, Erik L L Sonnhammer
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摘要

FunCoup 6(https://funcoup6.scilifelab.se/,出版后将为 https://funcoup.org)代表了全球功能关联网络的重大进展,旨在为研究人员提供功能耦合相互作用组的全面视图。这次更新引入了新的方法和集成工具,以改进网络推断和分析。FunCoup 6 的主要新进展包括:极大地扩展了基因调控联系的覆盖范围、无二进制贝叶斯训练新框架和新网站。FunCoup 6 集成了一个新工具,可使用 TOPAS 算法识别疾病和药物靶标模块。为了扩大该资源在生物医学研究中的实用性,它采用了 ANUBIX 和 EASE 算法进行通路富集分析。FunCoup 中独特的比较相互作用组学分析提供了网络保护的见解,现在用户可以只对齐同源物或独立查询每个物种的网络。对 23 个主要物种进行了无比对训练,此外还为 InParanoiDB 9 中的所有剩余 618 个物种生成了网络。伴随着这些进步,FunCoup 6 采用了全新设计的网站和更新的 API 功能,在功能基因组学研究领域迈出了关键的一步,为探索复杂的蛋白质相互作用提供了独特的功能。
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FunCoup 6: advancing functional association networks across species with directed links and improved user experience
FunCoup 6 (https://funcoup6.scilifelab.se/, will be https://funcoup.org after publication) represents a significant advancement in global functional association networks, aiming to provide researchers with a comprehensive view of the functional coupling interactome. This update introduces novel methodologies and integrated tools for improved network inference and analysis. Major new developments in FunCoup 6 include vastly expanding the coverage of gene regulatory links, a new framework for bin-free Bayesian training, and a new website. FunCoup 6 integrates a new tool for disease and drug target module identification using the TOPAS algorithm. To expand the utility of the resource for biomedical research, it incorporates pathway enrichment analysis using the ANUBIX and EASE algorithms. The unique comparative interactomics analysis in FunCoup provides insights of network conservation, now allowing users to align orthologs only or query each species network independently. Bin-free training was applied to 23 primary species, and in addition networks were generated for all remaining 618 species in InParanoiDB 9. Accompanying these advancements, FunCoup 6 features a new redesigned website, together with updated API functionalities, and represents a pivotal step forward in functional genomics research, offering unique capabilities for exploring the complex landscape of protein interactions.
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