Prediction of Nitrotyrosine Sites Based On Composition and Position Based Features

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dc.contributor.authorAhmad Waseem Ghauri
dc.date.accessioned2025-08-08T05:54:19Z
dc.date.available2025-08-08T05:54:19Z
dc.date.issued2018
dc.description.abstractClosely 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.
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/4673
dc.language.isoen_US
dc.publisherUMT, Lahore
dc.titlePrediction of Nitrotyrosine Sites Based On Composition and Position Based Features
dc.typeThesis
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