Addressing the problem of lysine glycation prediction in proteins via Recurrent Neural Networks
Ulices Que-Salinas,
Dulce Martinez-Peon,
Gerardo Maximiliano Mendez
et al.
Abstract:A distinguishing feature of the metabolic disorder diabetes involves elevated damage to cellular proteins. The primary form of alteration arises from the chemical interaction between glycating agents such as methylglyoxal and proteinaceous arginine/lysine residues, causing structural and functional disruptions in target proteins. In this study, a curated version of the CPLM database to implement a recurrent neural network strategy for the classification of lysine glycation has been utilized. By using one physi… Show more
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