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An adaptive strategy for the classification of g-protein coupled receptors
2007
SAIEE Africa Research Journal
One of the major problems in computational biology is the inability of existing classification models to incorporate expanding and new domain knowledge. The prohlem of static classification models is addressed in this paper by the introduction of incrcmelllal learning for problems in hioinformatics. Many machine learning 100is have been applied to Ihis problem using static machine learning structun:s such as neural networks or support vector machines that are unable to accoillmodate new
doi:10.23919/saiee.2007.9488130
fatcat:kcn7lxjblbhwbjga4mi7mmmuxy