Data Science Research to Support Stem Cell Therapy for Muscular Dystrophy

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Creator: 

Hernandez Salas, Karen Nathaly

Date: 

2018

Abstract: 

This thesis project focused on using a sequence-based, high-performance computational tool to design synthetic proteins and is part of current collaborative research on Duchenne Muscular Dystrophy (DMD). A possible treatment for DMD consists of injecting patients with healthy muscle satellite cells grown in tissue culture. However, such cells cannot currently be produced in quantity because they convert to muscle cells (differentiate) prematurely. Using InSiPS, the In-Silico Protein Synthesizer, protein sequences were designed to interact with target proteins and inhibit the protein-protein interaction proposed to regulate the premature differentiation. The resulting sequences were predicted to interact with the target proteins with high specificity (99.98%). Complementary biochemistry experiments indicated interactions with the intended target for two out of ten synthetic proteins. These results are being studied as part of the ongoing research seeking to develop a treatment for DMD.

Subject: 

Computer Science
Bioinformatics

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Computer Science: 
M.C.S.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Computer Science

Parent Collection: 

Theses and Dissertations

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