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BioSeq-Analysis2.0: an updated platform for analyzing DNA RNA and protein sequences at sequence level and residue level based on machine learning approaches

机译:BioSeq-Analysis2.0:一个更新的平台可基于机器学习方法在序列水平和残基水平上分析DNARNA和蛋白质序列

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摘要

As the first web server to analyze various biological sequences at sequence level based on machine learning approaches, many powerful predictors in the field of computational biology have been developed with the assistance of the BioSeq-Analysis. However, the BioSeq-Analysis can be only applied to the sequence-level analysis tasks, preventing its applications to the residue-level analysis tasks, and an intelligent tool that is able to automatically generate various predictors for biological sequence analysis at both residue level and sequence level is highly desired. In this regard, we decided to publish an important updated server covering a total of 26 features at the residue level and 90 features at the sequence level called BioSeq-Analysis2.0 ( ), by which the users only need to upload the benchmark dataset, and the BioSeq-Analysis2.0 can generate the predictors for both residue-level analysis and sequence-level analysis tasks. Furthermore, the corresponding stand-alone tool was also provided, which can be downloaded from . To the best of our knowledge, the BioSeq-Analysis2.0 is the first tool for generating predictors for biological sequence analysis tasks at residue level. Specifically, the experimental results indicated that the predictors developed by BioSeq-Analysis2.0 can achieve comparable or even better performance than the existing state-of-the-art predictors.
机译:作为第一个基于机器学习方法在序列水平上分析各种生物学序列的Web服务器,借助BioSeq-Analysis在计算生物学领域开发了许多强大的预测器。但是,BioSeq-Analysis只能应用于序列级分析任务,无法应用于残基级分析任务,而智能工具可以自动生成用于残基级和残基级的生物序列分析的各种预测因子。序列水平是非常需要的。在这方面,我们决定发布一个重要的更新服务器,该服务器涵盖了残基级的26个特征和序列级的90个特征,称为BioSeq-Analysis2.0(),通过该服务器,用户只需上传基准数据集, BioSeq-Analysis2.0可以为残基级分析和序列级分析任务生成预测因子。此外,还提供了相应的独立工具,可以从下载。据我们所知,BioSeq-Analysis2.0是第一个为残基水平的生物序列分析任务生成预测因子的工具。具体而言,实验结果表明,由BioSeq-Analysis2.0开发的预测器与现有的最新预测器相比可以实现相当甚至更好的性能。

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