Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India.
Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India.
J Mol Biol. 2023 Jul 15;435(14):167921. doi: 10.1016/j.jmb.2022.167921. Epub 2022 Dec 14.
Operons are groups of consecutive genes that transcribe together under the regulation of a common promoter. They influence protein regulation and various physiological pathways, making their accurate detection desirable. The detection of operons through experimental means is a laborious and financially intensive process. Therefore, human experts predict potential operons utilizing their prior knowledge of the genetic organization and functional correlation of the genes. However, with the rise in the number of completely sequenced genomes, the development of automated algorithms, tools, and web servers is highly preferred over manual detection for operon prediction. Currently available state-of-the-art algorithms use a deep learning-based model to predict if the adjacent genes belong to the same operons in the given genome. However, these require an understanding of programming knowledge and computational skills, making them not-very user friendly. In this study, we developed a user-friendly web service, Operon Finder, for on-the-fly prediction of operons using the deep learning method. The interface provides a facility for genome search, operon live-filtering, viewing operonic DNA sequences, downloading predicted results, and links for data retrieval from the NCBI (National Center for Biotechnology Information) database. The web server is available at https://www.iitg.ac.in/spkanaujia/operonfinder.html. The experimental methods and the implementation details are publicly available at https://github.com/SPKlab/Operon-Finder.
操纵子是一组连续的基因，在共同启动子的调控下一起转录。它们影响蛋白质调节和各种生理途径，因此准确检测它们是可取的。通过实验手段检测操纵子是一项费力且资金密集的过程。因此，人类专家利用他们对基因组织和基因功能相关性的先验知识来预测潜在的操纵子。然而，随着完全测序基因组数量的增加，自动化算法、工具和网络服务器的开发比手动检测更适合于操纵子预测。目前可用的最先进算法使用基于深度学习的模型来预测给定基因组中相邻基因是否属于同一操纵子。然而，这些算法需要理解编程知识和计算技能，因此不太用户友好。在这项研究中，我们开发了一个用户友好的网络服务 Operon Finder，用于使用深度学习方法进行操纵子的实时预测。该界面提供了基因组搜索、操纵子实时过滤、查看操纵子 DNA 序列、下载预测结果以及从 NCBI（国家生物技术信息中心）数据库检索数据的链接。该网络服务器可在 https://www.iitg.ac.in/spkanaujia/operonfinder.html 访问。实验方法和实现细节可在 https://github.com/SPKlab/Operon-Finder 上公开获取。
