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Lecturer

sinan s. mohammed sheet

Research Interests

Gender MALE
Place of Work Polytechnic College Mosul
Department Medical Equipment Techniques
Position Assit. Prof.
Qualification Ph.d
Speciality Biomedical engineering
Email sinan_sm76@ntu.edu.iq
Phone 07518096967
Address Mosul/ al-Sukar, Mosul, Mosul, Iraq
About Me

1 +

Best Ph.D student award

1 +

Best Paper award
working experience

Academic Qualification

Ph.D
Sep 11, 2019 - Dec 29, 2022

Doctor of Philosophy ( Biomedical Engineering )

Master
Jan 10, 2010 - Oct 27, 2011

UTM Malaysia
Medical instrumentation engineering

Bachelor
Sep 1, 1994 - Jul 1, 1999

Medical instrumentation engineering

Publications

A novel method for examining promoters using statistical analysis and artificial intelligence learning
Feb 3, 2026

Journal IAES International Journal of Artificial Intelligence (IJ-AI)

DOI 10.11591/ijai.v14.i5.pp4006-4016

Issue 5

Volume 14

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

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