WHISTLE server: A high-accuracy genomic coordinate-based machine learning platform for RNA modification prediction.

Journal: Methods (San Diego, Calif.)
Published Date:

Abstract

The primary sequences of DNA, RNA and protein have been used as the dominant information source of existing machine learning tools, especially for contexts not fully explored by wet-experimental approaches. Since molecular markers are profoundly orchestrated in the living organisms, those markers that cannot be unambiguously recovered from the primary sequence often help to predict other biological events. To the best of our knowledge, there is no current tool to build and deploy machine learning models that consider genomic evidence. We therefore developed the WHISTLE server, the first machine learning platform based on genomic coordinates. It features convenient covariate extraction and model web deployment with 46 distinct genomic features integrated along with the conventional sequence features. We showed that, when predicting mA sites from SRAMP project, the model integrating genomic features substantially outperformed those based on only sequence features. The WHISTLE server should be a useful tool for studying biological attributes specifically associated with genomic coordinates, and is freely accessible at: www.xjtlu.edu.cn/biologicalsciences/whi2.

Authors

  • Lian Liu
    Foshan University, Foshan 528000, China. lian2004@163.com.
  • Bowen Song
    Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX Liverpool, UK.
  • Kunqi Chen
    Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China.
  • Yuxin Zhang
    State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology , Sichuan University , Chengdu 610041 , People's Republic of China.
  • João Pedro de Magalhães
    Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK.
  • Daniel J Rigden
    Institute of Integrative Biology, University of Liverpool, L7 8TX Liverpool, UK.
  • Xiujuan Lei
  • Zhen Wei
    Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China.