Abstract
Optimally weighted fuzzy k-nearest neighbors (OWFKNN) algorithm has been used to predict proteins’ subcellular locations based on their amino acid composition, in this paper. The datasets used consists of two species which are 997 prokaryotic and 2427 eukaryotic protein sequences. The overall prediction accuracy achieved is about 88.5% for prokaryotic sequences and 86.2% for eukaryotic sequences in a jackknife test. Compared to other algorithms developed for the prediction of protein subcellular location, OWFKNN gives very satisfying results. Therefore, OWFKNN can be used as an alternative method to predict protein localization.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
