NetworkCommons: bridging data, knowledge, and methods to build and evaluate context-specific biological networks.

Victor Paton, Denes Türei, Olga Ivanova, Sophia Müller-Dott, Pablo Rodriguez-Mier, Veronica Venafra, Livia Perfetto, Martin Garrido-Rodriguez, Julio Saez-Rodriguez
{"title":"NetworkCommons: bridging data, knowledge, and methods to build and evaluate context-specific biological networks.","authors":"Victor Paton, Denes Türei, Olga Ivanova, Sophia Müller-Dott, Pablo Rodriguez-Mier, Veronica Venafra, Livia Perfetto, Martin Garrido-Rodriguez, Julio Saez-Rodriguez","doi":"10.1093/bioinformatics/btaf048","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>We present NetworkCommons, a platform for integrating prior knowledge, omics data, and network inference methods, facilitating their usage and evaluation. NetworkCommons aims to be an infrastructure for the network biology community that supports the development of better methods and benchmarks, by enhancing interoperability and integration.</p><p><strong>Availability and implementation: </strong>NetworkCommons is implemented in Python and offers programmatic access to multiple omics datasets, network inference methods, and benchmarking setups. It is a free software, available at https://github.com/saezlab/networkcommons, and deposited in Zenodo at https://doi.org/10.5281/zenodo.14719118.</p>","PeriodicalId":93899,"journal":{"name":"Bioinformatics (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846666/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btaf048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Summary: We present NetworkCommons, a platform for integrating prior knowledge, omics data, and network inference methods, facilitating their usage and evaluation. NetworkCommons aims to be an infrastructure for the network biology community that supports the development of better methods and benchmarks, by enhancing interoperability and integration.

Availability and implementation: NetworkCommons is implemented in Python and offers programmatic access to multiple omics datasets, network inference methods, and benchmarking setups. It is a free software, available at https://github.com/saezlab/networkcommons, and deposited in Zenodo at https://doi.org/10.5281/zenodo.14719118.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
网络共享:连接数据、知识和方法,以建立和评估特定环境的生物网络。
摘要:我们介绍的 NetworkCommons 是一个整合先验知识、omics 数据和网络推断方法的平台,可促进这些方法的使用和评估。NetworkCommons 的目标是成为网络生物学社区的基础设施,通过增强互操作性和集成性,支持开发更好的方法和基准:NetworkCommons 使用 Python 实现,可通过编程访问多个 omics 数据集、网络推理方法和基准设置。它是一款免费软件,可从 https://github.com/saezlab/networkcommons 获取,并存放在 Zenodo 中,网址为 https://doi.org/10.5281/zenodo.14719118 。补充数据:有关数据、知识、方法、评估策略及其实施的投稿指南、附加图表和说明可在补充数据和 NetworkCommons 文档(https://networkcommons.readthedocs.io/)中查阅。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
VDJ-Insights: simplifying the annotation of genomic immunoglobulin and T cell receptor regions. igv-reports: embedding interactive genomic visualizations in HTML reports to aid variant review. SpliceHarmonization: an integrated method for identifying RNA splicing events in therapeutics for splicing modulation. Evaluating deep learning based structure prediction methods on antibody-antigen complexes. Structure-preserving multivariate hypothesis testing for mass spectrometry imaging and single-cell data.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1