Browsing by Author "FATIMA AABID"

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    Phosphotyrosine site prediction using deep learning
    (UMT Lahore, 2022) FATIMA AABID
    Post-translational modification is one of the ways to enhance the genetic coding capacity to generate diversity in the respective proteomes. The phosphorylation of proteins intrigued computer scientists. Prediction of the protein site is simple but challenging to make an accurate prediction using it. Protein phosphorylation is a vital source for various cellular processes and one of the most fundamental types of a posttranslational modification. It is the addition of a phosphate group to the target residue. Proteins serine, threonine, and tyrosine are the most common phosphorylation; amongst these, tyrosine phosphorylation is the most frequent one and important for signal transduction in eukaryotic cells. One common approach is mass spectrometry. Another way for identification is the computational approach. Here, this research presents a novel computational predictor of phosphoTyrosine sites, adopting Chou’s 5-step rule. Different deep neural networks were used to train the model and then compared.