ncRNA_loc Web Service for identifying RNA-associated subcellular localizations

Introduction

A web servicer for identifying RNA-associated subcellular localizations. We extract multi-label classification datasets about RNA-associated subcellular localizations on four various of RNAs, and then construct subcellular localization datasets on four RNA categories. In order to study Homo sapiens, we further establish human RNA subcellular localization datasets. Furthermore, we utilize different nucleotide property composition models to extract effective features to adequately represent the important information of nucleotide sequences. Moreover, we fuse the multivariate information through multiple kernel learning based on Hilbert-Schmidt independence criterion. The optimal combined kernel can be put into an integration support vector machine model for identifying multi-label RNA subcellular localizations.

Publications

  1. Identify RNA-associated subcellular localizations based on multi-label learning using Chou’s 5-steps rule
    Cite this
    Hao Wang, Yijie Ding, Jijun Tang, Quan Zou, Fei Guo, 2021/1/15 - BMC Genomics

Credits

  1. Fei Guo fguo@tju.edu.cn
    Investigator

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

  2. Yijie DIng wuxi_dyj@163.com
    Developer

    School of Electronic and Information Engineering, Suzhou University of Science and Technology, China

  3. Hao Wang hzwh6910@163.com
    Developer

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

  4. Jijun Tang jtang@cse.sc.edu
    Contributor

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

  5. Zou Quan zouquan@nclab.net
    Contributor

    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, China

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Summary
AccessionBT007129
Tool TypeApplication
CategorySubcellular localization prediction
PlatformsWindows
TechnologiesPython3
User InterfaceWebpage
Input DataFASTA
Latest Release1.0 (May 29, 2021)
Download Count826
Country/RegionChina
Submitted ByFei Guo
Fundings

2018YFC0910400