Publications

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Journal Article
abd elaziz, M., Y. S. Moemen, A. E. Hassanien, and S. Xiong, "Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System, ", Scientific report (Nature) , vol. 1506, 2018. Abstract

The global prevalence of hepatitis C Virus (HCV) is approximately 3% and one-fifth of all HCV carriers live in the Middle East, where Egypt has the highest global incidence of HCV infection. Quantitative structure-activity relationship (QSAR) models were used in many applications for predicting the potential effects of chemicals on human health and environment. The adaptive neuro-fuzzy inference system (ANFIS) is one of the most popular regression methods for building a nonlinear QSAR model. However, the quality of ANFIS is influenced by the size of the descriptors, so descriptor selection methods have been proposed, although these methods are affected by slow convergence and high time complexity. To avoid these limitations, the antlion optimizer was used to select relevant descriptors, before constructing a nonlinear QSAR model based on the PIC50 and these descriptors using ANFIS. In our experiments, 1029 compounds were used, which comprised 579 HCVNS5B inhibitors (PIC50 < ~14) and 450 non-HCVNS5B inhibitors (PIC50 > ~14). The experimental results showed that the proposed QSAR model obtained acceptable accuracy according to different measures, where R2 was 0.952 and 0.923 for the training and testing sets, respectively, using cross-validation, while R2 LOO
was 0.8822 using leave-one-out (LOO).

Hassanien, A. E., Mostafa A. Salama, J. Platos, and V. Snásel, "Rough local transfer function for cardiac disorders detection using heart sounds. ", Logic Journal of the IGPL, vol. 23, issue 3, pp. 506-520, 2015. Website
Salama, M. A., O. S. Soliman, I. Maglogiannis, A. E. Hassanien, and A. A. Fahmy, "Rough set-based identification of heart valve diseases using heart sounds", Rough Sets and Intelligent Systems-Professor Zdzisław Pawlak in Memoriam: Springer Berlin Heidelberg, pp. 475–491, 2013. Abstract
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Salama, M. A., O. S. Soliman, I. Maglogiannis, A. E. Hassanien, and A. A. Fahmy, "Rough set-based identification of heart valve diseases using heart sounds", Rough Sets and Intelligent Systems-Professor Zdzisław Pawlak in Memoriam: Springer Berlin Heidelberg, pp. 475–491, 2013. Abstract
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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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El-Sehiemy, R. A., Mostafa Abdelkhalik El-hosseini, and A. E. Hassanien, "Volume 22• Issue 2• 2013", Studies in Informatics and Control-ICI Bucharest, 2013. Abstract
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Miscellaneous
Smolinski, T. G., M. G. Milanova, and A. - E. Hassanien, Applications of Computational Intelligence in Biology: Current Trends and Open Problems, : Springer, 2008. Abstract
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Smolinski, T. G., M. G. Milanova, and A. - E. Hassanien, Applications of Computational Intelligence in Biology: Current Trends and Open Problems, : Springer, 2008. Abstract
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Smolinski, T. G., M. G. Milanova, and A. - E. Hassanien, Computational Intelligence in Biomedicine and Bioinformatics: Current trends and applications, : Springer, 2009. Abstract
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Smolinski, T. G., M. G. Milanova, and A. - E. Hassanien, Computational Intelligence in Biomedicine and Bioinformatics: Current trends and applications, : Springer, 2009. Abstract
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Hassanien, A. E., M. M. Fouad, A. A. Manaf, M. Zamani, R. Ahmad, and J. Kacprzyk, Multimedia Forensics and Security: Foundations, Innovations, and Applications, : Springer, 2016. Abstract
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