ePlatypus:用于免疫基因组学数据计算分析的生态系统。

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad553
Tudor-Stefan Cotet, Andreas Agrafiotis, Victor Kreiner, Raphael Kuhn, Danielle Shlesinger, Marcos Manero-Carranza, Keywan Khodaverdi, Evgenios Kladis, Aurora Desideri Perea, Dylan Maassen-Veeters, Wiona Glänzer, Solène Massery, Lorenzo Guerci, Kai-Lin Hong, Jiami Han, Kostas Stiklioraitis, Vittoria Martinolli D'Arcy, Raphael Dizerens, Samuel Kilchenmann, Lucas Stalder, Leon Nissen, Basil Vogelsanger, Stine Anzböck, Daria Laslo, Sophie Bakker, Melinda Kondorosy, Marco Venerito, Alejandro Sanz García, Isabelle Feller, Annette Oxenius, Sai T Reddy, Alexander Yermanos
{"title":"ePlatypus:用于免疫基因组学数据计算分析的生态系统。","authors":"Tudor-Stefan Cotet,&nbsp;Andreas Agrafiotis,&nbsp;Victor Kreiner,&nbsp;Raphael Kuhn,&nbsp;Danielle Shlesinger,&nbsp;Marcos Manero-Carranza,&nbsp;Keywan Khodaverdi,&nbsp;Evgenios Kladis,&nbsp;Aurora Desideri Perea,&nbsp;Dylan Maassen-Veeters,&nbsp;Wiona Glänzer,&nbsp;Solène Massery,&nbsp;Lorenzo Guerci,&nbsp;Kai-Lin Hong,&nbsp;Jiami Han,&nbsp;Kostas Stiklioraitis,&nbsp;Vittoria Martinolli D'Arcy,&nbsp;Raphael Dizerens,&nbsp;Samuel Kilchenmann,&nbsp;Lucas Stalder,&nbsp;Leon Nissen,&nbsp;Basil Vogelsanger,&nbsp;Stine Anzböck,&nbsp;Daria Laslo,&nbsp;Sophie Bakker,&nbsp;Melinda Kondorosy,&nbsp;Marco Venerito,&nbsp;Alejandro Sanz García,&nbsp;Isabelle Feller,&nbsp;Annette Oxenius,&nbsp;Sai T Reddy,&nbsp;Alexander Yermanos","doi":"10.1093/bioinformatics/btad553","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.</p><p><strong>Results: </strong>Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics, and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.</p><p><strong>Availability and implementation: </strong>Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.</p>","PeriodicalId":8903,"journal":{"name":"Bioinformatics","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518073/pdf/","citationCount":"0","resultStr":"{\"title\":\"ePlatypus: an ecosystem for computational analysis of immunogenomics data.\",\"authors\":\"Tudor-Stefan Cotet,&nbsp;Andreas Agrafiotis,&nbsp;Victor Kreiner,&nbsp;Raphael Kuhn,&nbsp;Danielle Shlesinger,&nbsp;Marcos Manero-Carranza,&nbsp;Keywan Khodaverdi,&nbsp;Evgenios Kladis,&nbsp;Aurora Desideri Perea,&nbsp;Dylan Maassen-Veeters,&nbsp;Wiona Glänzer,&nbsp;Solène Massery,&nbsp;Lorenzo Guerci,&nbsp;Kai-Lin Hong,&nbsp;Jiami Han,&nbsp;Kostas Stiklioraitis,&nbsp;Vittoria Martinolli D'Arcy,&nbsp;Raphael Dizerens,&nbsp;Samuel Kilchenmann,&nbsp;Lucas Stalder,&nbsp;Leon Nissen,&nbsp;Basil Vogelsanger,&nbsp;Stine Anzböck,&nbsp;Daria Laslo,&nbsp;Sophie Bakker,&nbsp;Melinda Kondorosy,&nbsp;Marco Venerito,&nbsp;Alejandro Sanz García,&nbsp;Isabelle Feller,&nbsp;Annette Oxenius,&nbsp;Sai T Reddy,&nbsp;Alexander Yermanos\",\"doi\":\"10.1093/bioinformatics/btad553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.</p><p><strong>Results: </strong>Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics, and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.</p><p><strong>Availability and implementation: </strong>Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.</p>\",\"PeriodicalId\":8903,\"journal\":{\"name\":\"Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2023-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518073/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/bioinformatics/btad553\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btad553","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

摘要

动机:系统免疫学方法的成熟需要新颖透明的计算框架,能够以可复制的方式集成各种数据模式。结果:在这里,我们介绍了用于免疫基因组学数据分析的ePlatypus计算免疫学生态系统,重点是适应性免疫库和单细胞测序。ePlatypus是一个开源的基于网络的平台,提供编程教程和综合数据库,帮助阐明B细胞和T细胞克隆选择的特征。此外,该生态系统连接了与单细胞免疫库和计算免疫学的其他方面相关的新的和已建立的生物信息学管道,如预测配体-受体相互作用、结构建模、模拟、机器学习、图论、假时间、空间转录组学和系统发育学。ePlatypus生态系统有助于深入了解计算免疫学和免疫基因组学,并促进开放科学。可用性和实现:本文中使用的Platypus代码可以在github.com/alexyermanos/Platypus上找到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
ePlatypus: an ecosystem for computational analysis of immunogenomics data.

Motivation: The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.

Results: Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics, and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.

Availability and implementation: Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
期刊最新文献
MEHunter: Transformer-based mobile element variant detection from long reads PQSDC: a parallel lossless compressor for quality scores data via sequences partition and Run-Length prediction mapping. MUSE-XAE: MUtational Signature Extraction with eXplainable AutoEncoder enhances tumour types classification. CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics CORDAX web server: An online platform for the prediction and 3D visualization of aggregation motifs in protein sequences.
×
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:481959085
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