Prediction of Nitrotyrosine Sites Based On Composition and Position Based Features

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Date
2018
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UMT, Lahore
Abstract
Closely related to causes of various diseases such as rheumatoid arthritis, septic shock, and coeliac disease; tyrosine nitration is considered as one of the most important post translational modification in proteins. Inside a cell, such modifications occur accurately by the action of sophisticated cellular machinery. This task is accomplished by specific enzymes present in endoplasmic reticulum. The identification of potential tyrosine residues in a protein primary sequence which can be nitrated is a challenging task. To counter the prevailing, laborious and time-consuming experimental approaches, here we introduce a novel computational model. Based on experimentally verified tyrosine nitration sites, they are transformed to their feature vectors.
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