School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China.
Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, China.
Nucleic Acids Res. 2019 Nov 18;47(20):e127. doi: 10.1093/nar/gkz740.
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 (http://bliulab.net/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 http://bliulab.net/BioSeq-Analysis2.0/download/. 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.
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序列的网络服务器,BioSeq-Analysis 协助开发了许多计算生物学领域的强大预测器。然而,BioSeq-Analysis 只能应用于序列水平的分析任务,无法应用于残基水平的分析任务,因此人们非常需要一种能够自动为生物序列在残基水平和序列水平上的分析生成各种预测器的智能工具。有鉴于此,我们决定发布一个名为 BioSeq-Analysis2.0 的重要更新服务器,总共包含 26 个残基水平特征和 90 个序列水平特征(http://bliulab.net/BioSeq-Analysis2.0/),用户只需上传基准数据集,BioSeq-Analysis2.0 就可以为残基水平和序列水平的分析任务生成预测器。此外,还提供了相应的独立工具,可从 http://bliulab.net/BioSeq-Analysis2.0/download/ 下载。据我们所知,BioSeq-Analysis2.0 是第一个用于生成生物序列分析任务残基水平预测器的工具。具体来说,实验结果表明,BioSeq-Analysis2.0 开发的预测器可以达到与现有最先进的预测器相当或更好的性能。