FunCoup 6: advancing functional association networks across species with directed links and improved user experience

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Davide Buzzao, Emma Persson, Dimitri Guala, Erik L L Sonnhammer
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引用次数: 0

Abstract

FunCoup 6 (https://funcoup.org) 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.
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
FunCoup 6 (https://funcoup.org) 是全球功能关联网络的重大进步,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 中独特的交互组学比较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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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