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Updated: May 1, 2026
Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry CCMS
Published on: December 20, 2010
m1A-Ensem: accurate identification of 1-methyladenosine sites through ensemble models
Muhammad Taseer Suleman1, Fahad Alturise2, Tamim Alkhalifah3
1Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore, 54770, Pakistan.
Background:
1-methyladenosine (m1A) is a variant of methyladenosine that holds a methyl substituent in the 1st position having a prominent role in RNA stability and human metabolites.
Objective:
Traditional approaches, such as mass spectrometry and site-directed mutagenesis, proved to be time-consuming and complicated.
Methodology:
The present research focused on the identification of m1A sites within RNA sequences using novel feature development mechanisms. The obtained features were used to train the ensemble models, including blending, boosting, and bagging. Independent testing and k-fold cross validation were then performed on the trained ensemble models.
Results:
The proposed model outperformed the preexisting predictors and revealed optimized scores based on major accuracy metrics.
Conclusion:
For research purpose, a user-friendly webserver of the proposed model can be accessed through https://taseersuleman-m1a-ensem1.streamlit.app/ .
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