鉴定(生物学)
计算生物学
基因表达
基因
表达式(计算机科学)
数据库
生物
计算机科学
生物信息学
遗传学
程序设计语言
植物
作者
Ni Kuang,Qinfeng Ma,Xiao Zheng,Xuehang Meng,Zhaoyu Zhai,Qiang Li,Jianbo Pan
标识
DOI:10.1016/j.csbj.2024.06.003
摘要
Gene expression is dynamic and varies at different stages of processes. The identification of gene profiles with temporal-specific expression patterns can provide valuable insights into ongoing biological processes, such as the cell cycle, cell development, circadian rhythms, or responses to external stimuli such as drug treatments or viral infections. However, currently, no database defines, identifies or archives gene profiles with temporal-specific expression patterns. Here, using a high-throughput regression analysis approach, eight linear and nonlinear parametric models were fitted to gene expression profiles from time-series experiments to identify eight types of gene profiles with temporal-specific expression patterns. We curated 2,684 time-series transcriptome datasets and identified 2,644,370 gene profiles exhibiting temporal-specific expression patterns. The results were stored in the database GeTeSEPdb (gene profiles with temporal-specific expression patterns database, http://www.inbirg.com/GeTeSEPdb/). Moreover, we implemented an online tool to identify gene profiles with temporal-specific expression patterns from user-submitted data. In summary, GeTeSEPdb is a comprehensive web service that can be used to identify and analyse gene profiles with temporal-specific expression patterns. This approach facilitates the exploration of transcriptional changes, temporal patterns of responses, and causal relationships between genes. We firmly believe that GeTeSEPdb will become a valuable resource for biologists and bioinformaticians.
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