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Updated: May 7, 2026
09:37
An Integrated Approach for Microprotein Identification and Sequence Analysis
Published on: July 12, 2022
A context evaluation approach for structural comparison of proteins using cross entropy over n-gram modelling
Jafar Razmara1, Safaai B Deris, Sepideh Parvizpour
1Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.
Computers in Biology and Medicine
|September 17, 2013
Summary
This study presents a novel text modeling technique for protein structural comparison. It efficiently predicts protein function by analyzing sequence similarities, offering high speed and accuracy comparable to existing tools.
Area of Science:
- Structural Biology
- Computational Biology
- Bioinformatics
Background:
- Protein structural comparison is crucial for predicting protein function.
- Developing new, efficient methods for structural comparison remains an active research area.
Purpose of the Study:
- To introduce a novel text modeling-based technique for protein structural comparison.
- To evaluate the efficiency and accuracy of this new method.
Main Methods:
- Modeling protein secondary and tertiary structures into linear sequences.
- Utilizing n-gram modeling from computational linguistics to capture sequence regularities.
- Employing cross-entropy for measuring sequence similarities.
Main Results:
- The method demonstrates high running speed, comparable to linear encoding methods like 3D-BLAST.
- Accuracy is on par with high-accuracy comparison tools such as CE and TM-align.
- The algorithm exhibits high overall efficiency compared to state-of-the-art methods.
Conclusions:
- The text modeling approach offers an efficient and accurate method for protein structural comparison.
- This technique provides a valuable alternative for analyzing protein structures and predicting functions.
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