Introducing CHiDO-A No Code Genomic Prediction software implementation for the characterization and integration of driven omics.

IF 3.9 2区 生物学 Q1 GENETICS & HEREDITY Plant Genome Pub Date : 2024-10-24 DOI:10.1002/tpg2.20519
Francisco González, Julián García-Abadillo, Diego Jarquín
{"title":"Introducing CHiDO-A No Code Genomic Prediction software implementation for the characterization and integration of driven omics.","authors":"Francisco González, Julián García-Abadillo, Diego Jarquín","doi":"10.1002/tpg2.20519","DOIUrl":null,"url":null,"abstract":"<p><p>Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties that can be more resilient to the increasingly variable climatic conditions. Leveraging large and diverse datasets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces characterization and integration of driven omics (CHiDO), an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process datasets, CHiDO's intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform's mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Genome","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/tpg2.20519","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0

Abstract

Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties that can be more resilient to the increasingly variable climatic conditions. Leveraging large and diverse datasets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces characterization and integration of driven omics (CHiDO), an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process datasets, CHiDO's intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform's mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.

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
介绍 CHiDO--无代码基因组预测软件实现,用于表征和整合驱动的全息图学。
气候变化改变了对作物生长至关重要的环境条件,对全球粮食安全构成了重大挑战。植物育种人员可以通过开发抗逆性更强的作物品种,在缓解这些挑战方面发挥关键作用;然而,这些工作需要投入大量的资源和时间。为此,当务之急是利用当前的技术,将大量的生物和环境数据集吸收到预测模型中,以加快改良新品种的研究、开发和发布,使其能够更好地适应日益多变的气候条件。利用大型和多样化的数据集可以改进对环境刺激和基因组脉冲引起的表型反应的描述。更好地表征这些信号有可能提高我们在天气和/或土壤条件变化时高精度预测性状表现的能力。本文介绍了表征和整合驱动的 omics(CHiDO),这是一个易于使用、无需代码的平台,旨在整合各种 omics 数据集,并有效地模拟它们之间的相互作用。CHiDO 具有整合和处理数据集的灵活性,其直观的界面使用户能够探索历史数据、提出假设,并针对未来情况优化数据收集策略。该平台的使命是强调全球可访问性,为不具备数据处理和数据分析专业能力的情况提供民主化的统计解决方案。
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
Plant Genome
Plant Genome PLANT SCIENCES-GENETICS & HEREDITY
CiteScore
6.00
自引率
4.80%
发文量
93
审稿时长
>12 weeks
期刊介绍: The Plant Genome publishes original research investigating all aspects of plant genomics. Technical breakthroughs reporting improvements in the efficiency and speed of acquiring and interpreting plant genomics data are welcome. The editorial board gives preference to novel reports that use innovative genomic applications that advance our understanding of plant biology that may have applications to crop improvement. The journal also publishes invited review articles and perspectives that offer insight and commentary on recent advances in genomics and their potential for agronomic improvement.
期刊最新文献
Genome-wide association study uncovers pea candidate genes and metabolic pathways involved in rust resistance. Introducing CHiDO-A No Code Genomic Prediction software implementation for the characterization and integration of driven omics. Studies of genetic diversity and genome-wide association for vitamin C content in lettuce (Lactuca sativa L.) using high-throughput SNP arrays. Translating weighted probabilistic bits to synthetic genetic circuits. Functional analysis of PagERF021 gene in salt stress tolerance in Populus alba × P. glandulosa.
×
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