Clustering techniques Machine learning Bioinformatics Networking

[J3] Matar, J., El Khoury, H., Charr, JC., Guyeux, C., & Chrétien, S. (2025). Biological Sequence Clustering: Novel Approaches a Comparative Study. SN COMPUT. SCI. 6, 369. DOI: 10.1007/s42979025039056 [J2] Matar, J., El Khoury, H., Charr, JC., Guyeux, C., & Chrétien, S. (2024). Optimized Spectral Clustering Methods for Potentially Divergent Biological Sequences. Scientific Inquiry Review (SIR), Vol. 8, No.3. pp. 5887. DOI: 10.32350/sir.83.03 [J1] Matar, J., El Khoury, H., Charr, JC., Guyeux, C., & Chrétien, S. (2019). SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences. Computers in Biology and Medicine, 114, 103439. DOI: 10.1016/j.compbiomed.2019.103439 [C3] Matar, J., & El Khoury, H., Charr, JC., & Guyeux, C. (2025). Revisiting spectral clustering: assessments and extended capabilities. Proceedings of 2025 5th IEEE Middle East and North Africa Communications Conference (MENACOMM), Byblos, Lebanon: February 2022, 2025. IEEE Xplore 2025, pp. 16. DOI: 10.1109/MENACOMM62946.2025.10911002 [C2] Matar, J., & El Khoury, H., Charr, JC., & Guyeux, C. (2021). Impact of eigensolvers on spectral clustering. Proceedings of 2021 3rd IEEE Middle East and North Africa COMMunications Conference (MENACOMM 2021), Agadir, Morocco: December 0305, 2021. IEEE Xplore 2021, pp. 4953. DOI: 10.1109/MENACOMM50742.2021.9678223