MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm.
Protein phosphorylation is essential in various signal transduction and cellular processes. To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. In this study, a...
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| Format: | Article |
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Public Library of Science (PLoS)
2024-11-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012607 |
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| author | Chao Wang Quan Zou |
| author_facet | Chao Wang Quan Zou |
| author_sort | Chao Wang |
| collection | DOAJ |
| description | Protein phosphorylation is essential in various signal transduction and cellular processes. To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. In this study, a novel tool called MFPSP is developed for phosphorylation site prediction in multi-fungal species. The amino acids sequence features were derived from physicochemical and distributed information, and an offspring competition-based genetic algorithm was applied for choosing the most effective feature subset. The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. Feature contribution and interaction exploration indicating the proposed model is efficient in uncovering concealed patterns within sequence. We anticipate MFPSP to serve as a valuable bioinformatics tool and benefiting practical experiments by pre-screening potential phosphorylation sites and enhancing our functional understanding of phosphorylation modifications in fungi. The source code and datasets are accessible at https://github.com/AI4HKB/MFPSP/. |
| format | Article |
| id | doaj-art-f1537f5f1e014d71adb2f9fda5ee9aa5 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-f1537f5f1e014d71adb2f9fda5ee9aa52025-08-20T02:21:47ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582024-11-012011e101260710.1371/journal.pcbi.1012607MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm.Chao WangQuan ZouProtein phosphorylation is essential in various signal transduction and cellular processes. To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. In this study, a novel tool called MFPSP is developed for phosphorylation site prediction in multi-fungal species. The amino acids sequence features were derived from physicochemical and distributed information, and an offspring competition-based genetic algorithm was applied for choosing the most effective feature subset. The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. Feature contribution and interaction exploration indicating the proposed model is efficient in uncovering concealed patterns within sequence. We anticipate MFPSP to serve as a valuable bioinformatics tool and benefiting practical experiments by pre-screening potential phosphorylation sites and enhancing our functional understanding of phosphorylation modifications in fungi. The source code and datasets are accessible at https://github.com/AI4HKB/MFPSP/.https://doi.org/10.1371/journal.pcbi.1012607 |
| spellingShingle | Chao Wang Quan Zou MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. PLoS Computational Biology |
| title | MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. |
| title_full | MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. |
| title_fullStr | MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. |
| title_full_unstemmed | MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. |
| title_short | MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. |
| title_sort | mfpsp identification of fungal species specific phosphorylation site using offspring competition based genetic algorithm |
| url | https://doi.org/10.1371/journal.pcbi.1012607 |
| work_keys_str_mv | AT chaowang mfpspidentificationoffungalspeciesspecificphosphorylationsiteusingoffspringcompetitionbasedgeneticalgorithm AT quanzou mfpspidentificationoffungalspeciesspecificphosphorylationsiteusingoffspringcompetitionbasedgeneticalgorithm |