从二元化人类口腔微生物数据的预测年龄与一组分类器组合在一起
Yuxiang Zhou1, Yanyun Wang2, Benyang Xiao1
1Department of Forensic Genetics, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China.
mSystems
|October 31, 2025
概括
人口微生物组随着年龄的增长而发生变化,这项研究开发了一种使用二元化微生物数据的集合模型,以高精度预测时间年龄. 这种方法对未来基于微生物组的年龄预测研究有希望.
科学领域:
- 微生物学 微生物学
- 老年学是一门学科.
- 生物信息学是一种生物信息学.
背景情况:
- 人类微生物组的组成随年龄而变化.
- 关于口腔微生物组与衰老的关联及其预测潜力的研究有限.
- 年龄是影响微生物变异的重要因素.
研究的目的:
- 调查口腔微生物组与时间年龄之间的相关性.
- 使用口腔微生物组数据开发和验证一个可靠的年龄预测模型.
- 为了比较口腔微生物组分析的不同数据处理方法的性能.
主要方法:
- 分析了来自150名年龄在6-78岁的人口微生物组样本.
- 利用多变量变量分析 (PERMANOVA) 来识别与年龄相关的微生物变异.
- 在二元化口腔微生物数据上开发了一个使用 eXtreme Gradient Boosting (XGBoost) 和 32 个分类器的整体模型.
主要成果:
- 随着年龄的增长,物种丰富度和Chao1指数显著增加.
- 整体模型在一个独立的验证集上实现了7.20年的平均绝对误差 (MAE).
- 随着样本规模的增加 (2550人),MAE减少到4.80年,超过了以前的模型.
结论:
- 二元化口腔微生物数据与整体建模相结合,是人类年龄预测的一个有希望的方法.
- 开发的基于XGBoost的组合模型在年龄预测中表现出卓越的性能和稳定性.
- 这些发现为未来研究基于微生物组的年龄估计提供了基础.
更多相关视频
11:09An Analytical Tool-box for Comprehensive Biochemical, Structural and Transcriptome Evaluation of Oral Biofilms Mediated by Mutans Streptococci
Published on: January 25, 2011
18.1K
08:56Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
Published on: January 13, 2023
2.8K
相关概念视频
01:29Modern Molecular Taxonomy
536
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
536
01:24Microbial Classification System
831
Classification is the process of organizing organisms into hierarchically inclusive groups based on their phenotypic similarities or evolutionary relationships. A species comprises one or more strains, and closely related species are grouped into genera. Genera are further classified into families, families into orders, orders into classes, and so forth, up to the domain level, which is the broadest taxonomic rank derived from a combination of phenotypic and genotypic data.The nomenclature of...
831
01:20Applications of Molecular Taxonomy
467
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
467