MARS和RNAcmap3:所有可能的RNA序列的主数据库与RNAcmap集成,用于RNA同质性搜索
Ke Chen1,2,3,4, Thomas Litfin5, Jaswinder Singh1
1Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.
Genomics, proteomics & bioinformatics
|June 14, 2024
概括
研究人员开发了所有可能的RNA序列 (MARS) 主数据库,这是对非编码RNA (ncRNA) 同性学搜索的全面资源. 这个新的数据库显著改善了RNA序列对齐和结构推理能力.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 像AlphaFold2这样的蛋白质结构预测工具利用来自大型序列数据库的共同进化数据.
- 现有的核酸数据库缺乏整合,阻碍了对RNA序列的全面同质性搜索.
- 非编码RNAs (ncRNAs) 起着至关重要的作用,但它们的功能和结构分析通常受到数据库可访问性的限制.
研究的目的:
- 创建一个整合和显著更大的数据库,用于RNA序列同质性搜索.
- 开发一种新的策略,以改善 ncRNAs 的同质性搜索和多重序列对齐 (MSA) 生成.
- 提高ncRNAs的结构和功能推理的准确性和灵敏性.
主要方法:
- 整合了来自RNAcentral,MG-RAST,GWH,MGnify和NCBI的nt数据库的各种RNA序列数据.
- 开发了所有可能的RNA序列 (MARS) 主数据库,比NCBI的nt数据库增加了20倍.
- 实施了一种新的分割搜索策略,用于增强同质检测,并使用RNAcmap工具进行自动对齐.
主要成果:
- 火星比现有的核酸数据库大得多,可以进行更深入的同源性搜索.
- 新的数据集和分割搜索策略显著优于当前最先进的同类搜索技术.
- 与许多结构化RNA手动策划的Rfam对齐相比,产生了更准确和更敏感的多重序列对齐 (MSA).
结论:
- 火星为推进ncRNA研究提供了一个强大的资源.
- 与RNAcmap相结合的MARS数据库有助于改善ncRNAs的结构和功能推断.
- 这种资源对于开发基于MSA的先进RNA语言模型是有价值的.
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