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A Systematic Approach for Biomarker Identification in Autism Spectrum Disorder based on Machine learning

Ashraf Talesh, Mahdi | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 54247 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Jafari Siavoshani, Mahdi; Kavousi, Kaveh; Ohadi, Mina
  7. Abstract:
  8. Autism spectrum disorder (ASD) is a strong genetic perturbation that encompasses a wide range of clinical symptoms, including functional at different regions of the brain, repetitive behaviors, and interests, weaknesses in social relationships, some sensitivities to environmental factors and etc. Genetic complexity and the impact of environmental factors put the disease in the category of Level 1 complex developmental disorders.We proposed a pilot, combined, and highly effective structure to identify biomarkers in the autism spectrum disorder that could be extended to other diseases that have a similar genetic architecture with autism. We also develop a Gene-tissue interaction network to investigate our genes in 4 brain tissues as the first tissues to be affected by ASD and a gene-unctional network to diagnose high-risk biological processes in the autism spectrum disorder. Furthermore, we demonstrate that our 10 high-ranking genes were enriched in neurological diseases rather than non-neurological diseases based on the ranking method that we used. Then we performed a genome-wide short tandem repeat analysis (GWSTRA) on 479 probands from Quad families as part of Simon Simplex collection, each of which at least has one child affected with an autism spectrum disorder, and 312 individuals from the 1000 genome project as control samples. Preliminary studies show that about 3,000 distinct STR as biomarkers have been identified in case-control populations, which were proposed for the first time as proband-specific alleles. The results of our pilot study show a meaningful correlation between the results of our network-based study and the results of high throughput data which can be used as a practical study method
  9. Keywords:
  10. Machine Learning ; Autism Spectrum Disorders (ASD) ; Short Tandem Repeat Analysis (STRA) ; Genome-Wide Short Tandem Repeat Analysis (GWSTRA) ; Biomarker

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