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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Sheet, Sinan Salim Mohammed
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Computer Science & IT Engineering

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A novel method for examining promoters using statistical analysis and artificial intelligence learning Sheet, Sinan Salim Mohammed; Al-Hatab, Marwa Mawfaq Mohamedsheet; Qasim, Maysaloon Abed
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp4006-4016

Abstract

Accurately classifying promoters has become a significant focus in bioinformatics research. Although numerous studies have attempted to address this challenge, the performance of existing methods still leaves room for improvement this study, statistical feature analysis has been applied to the features that have been developed in our previous work. This approach extracted additional informative features from basic sequence characteristics and then used them together with the original and newly engineered features. Utilizing statistical feature analysis enhanced key patterns, which lead to an improvement in the accuracy of the promoter classification. Results demonstrated that our proposed method outperforms other models that use only basic features. The value of the area under the curve (AUC) of 0.83958 achieved when using the combined feature set confirmed the effectiveness of our approach. Furthermore, the AUC value reached 1 when these optimized features were used with naive Bayes (NB) classifier, referring to the strength of incorporating statistical analysis into feature design.
Co-Authors Al-Hatab, Marwa Mawfaq Mohamedsheet Qasim, Maysaloon Abed