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

Lian Liu, Bowen Song, Kunqi Chen, Yuxin Zhang, João Pedro de Magalhães, Daniel J. Rigden, Xiujuan Lei*, Zhen Wei

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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 m6A 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.

Original languageEnglish
Pages (from-to)378-382
Number of pages5
Publication statusPublished - Jul 2022


  • Epitranscriptome
  • Genomic coordinate
  • Web server

Cite this