An effective fast conventional pattern measure-based suffix feature selection to search gene expression data
by A. Surendar; M. Arun; A. Mahabub Basha
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 39, No. 3, 2022

Abstract: Biomedical gene sequences are incompletely or erroneously annotated because of a lack of experimental evidence or prior functional knowledge in sequence datasets. Identifying the genomic useful selections instead of relying on correlations across large experimental datasets or sequence similarity remains a problem. This study proposes a fast conventional suffix feature pattern search (FcsFPs) algorithm for searching the gene sequence from expression data using fast feature pattern by measuring the conventionality of search accuracy from gene expression dataset. The aim is to obtain an efficient search algorithm. In this case, features from state matrix and sequence centres are described in the form of a string and the assignment of points to different sequences is done by suffix term search. Overall, the conventional pattern selection reduces computing complexity of fast gene search, improves the accuracy of searching accuracy, and reduces time complexity and the dimensionality of nonlinear gene expression data.

Online publication date: Mon, 18-Jul-2022

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