Prediction of nitrosocysteine sites using position and composition variant features
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Date
2017
Authors
Journal Title
Journal ISSN
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Publisher
University of Management and Technology Lahore
Abstract
Protein S-nitrosylation, a significant posttranslational modification of protein, involves the addition of nitrogen oxide group to cysteine thiols to form S-nitrosocysteine. Growing evidence has suggested that S-nitrosylation plays a major role in numerous human diseases. So, it is highly anticipated for the intuition into biological research and drug discovery to develop such techniques for timely identification of S-nitrosylated proteins. The proposed system endeavors a novel strategy based on numerous intellectual computational method for the identification of S-nitrosocystiene site from a protein sequence. Statistical moments were used to extract the features and built a multilayer neural network model using Gradient Descending and Adaptive Learning Algorithm. The comparison results on the-state-of-the-art benchmark datasets have shown that this proposed scheme is very propitious, accurate and exceptionally effective for the prediction of S-nitrosocystiene in protein sequence
Description
Supervised by:Dr. Yaser Daanial Khan and Dr. Nouman Rasool
Keywords
S-nitrosylation, Drug discovery, MS Thesis