Publication: Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
| dc.contributor.author | Ibrahim, Al-Zaidi Mohammed Khaleel | |
| dc.date.accessioned | 2026-02-19T02:16:48Z | |
| dc.date.available | 2026-02-19T02:16:48Z | |
| dc.date.issued | 2024-11 | |
| dc.description.abstract | Proteins are essential to life, impacting many aspects of human existence. Recent advances in next-generation sequencing technologies have generated a vast amount of data online. However, scholars face the challenge of navigating this information and managing the complex computations needed for comparing protein sequences. Sequence alignment is crucial in this context, with significant implications for improving early disease diagnosis and pharmaceutical engineering. Multiple sequence alignment (msa) is a vital tool in bioinformatics for analyzing growing amounts of sequence data. However, finding similarities across large databases is an np-hard problem, meaning it is extremely difficult and time-consuming to solve exactly in real time. This highlights the need for faster and more accurate methods. The metaheuristic paradigm has recently captured significant attention amid the diverse approaches to address highly complex problems like the msa. A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. Consequently, the hho algorithm has been chosen as a potential remedy to confront the accuracy dilemmas intrinsic to msa. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/23627 | |
| dc.title | Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment | |
| dc.type | Resource Types::text::thesis::doctoral thesis | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |