Alternative Splicing (AS) is a process that is believed to have links to cellular function changes and some diseases in humans. Although AS was first discovered in the 1970s, not much research has been conducted on its role in functional implications on the proteome level. This study aims to use PIPE, a protein-protein interaction prediction algorithm, along with a tissue expression dataset to build a pipeline that differentiates between AS isoform products by analyzing isoform sequence changes, functional changes, and tissue expression changes that AS introduces. The study found that isoform sequence changes in alternative isoforms tend to be conserved deletions of amino-acid sub-sequences. The study also found that there is a statistically significant overlap between PIPE-predicted protein-protein interaction (PPI) network changes and tissue expression changes of alternatively spliced isoforms (ASIs) relative to their canonical isoforms (CIs) with a p-value of 8.25×10 −5 . Finally, among the analysis pipeline top ten genes with predicted significant ASIs' PPI network changes, LMO2, THOC2, and UBE2L3 are genes that were suspected of having links to different diseases such as basel-type breast cancer, intellectual disability (ID) and numerous autoimmune diseases according to literature studies. i Firstly, I would like to thank my supervisor Dr. Frank Dehne for his outstanding support throughout my Master's degree. Dr. Dehne provided me with invaluable advice, support, and kindness during my Master's journey. I could not have asked for a better supervisor.
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