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首页> 美国卫生研究院文献>Nucleic Acids Research >OligoMinerApp: a web-server application for the design of genome-scale oligonucleotide in situ hybridization probes through the flexible OligoMiner environment
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OligoMinerApp: a web-server application for the design of genome-scale oligonucleotide in situ hybridization probes through the flexible OligoMiner environment

机译：OligoMinerApp：一个网络服务器应用程序用于通过灵活的OligoMiner环境设计基因组规模的寡核苷酸原位杂交探针

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摘要

Fluorescence hybridization (FISH) is a powerful single-cell technique that harnesses nucleic acid base pairing to detect the abundance and positioning of cellular RNA and DNA molecules in fixed samples. Recent technology development has paved the way to the construction of FISH probes entirely from synthetic oligonucleotides (oligos), allowing the optimization of thermodynamic properties together with the opportunity to design probes against any sequenced genome. However, comparatively little progress has been made in the development of computational tools to facilitate the oligos design, and even less has been done to extend their accessibility. OligoMiner is an open-source and modular pipeline written in Python that introduces a novel method of assessing probe specificity that employs supervised machine learning to predict probe binding specificity from genome-scale sequence alignment information. However, its use is restricted to only those people who are confident with command line interfaces because it lacks a Graphical User Interface (GUI), potentially cutting out many researchers from this technology. Here, we present OligoMinerApp ( ), a web-based application that aims to extend the OligoMiner framework through the implementation of a smart and easy-to-use GUI and the introduction of new functionalities specially designed to make effective probe mining available to everyone.
机译：荧光杂交（FISH）是一种功能强大的单细胞技术，可利用核酸碱基配对来检测固定样本中细胞RNA和DNA分子的丰度和位置。最近的技术发展为完全由合成寡核苷酸（寡核苷酸）构建FISH探针铺平了道路，从而可以优化热力学性质，并有机会设计针对任何测序基因组的探针。但是，在促进寡核苷酸设计的计算工具的开发方面，进展相对较小，而在扩展寡核苷酸的可访问性方面所做的工作甚至很少。 OligoMiner是用Python编写的开放源代码和模块化管道，它引入了一种评估探针特异性的新方法，该方法采用有监督的机器学习来根据基因组规模的序列比对信息来预测探针结合特异性。但是，它的使用仅限于对命令行界面有信心的人，因为它缺少图形用户界面（GUI），这可能使许多研究人员无法使用该技术。在这里，我们介绍OligoMinerApp（），这是一个基于Web的应用程序，旨在通过实现一个智能且易于使用的GUI来扩展OligoMiner框架，并引入专门旨在使每个人都可以使用有效的探针挖掘功能的新功能。

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