Title

Visualizing Genetic Influence on Autism Spectrum Disorder (ASD) Diagnosis: The Roles of Colors and High Dimensional Graphs

Presenter Information

Scott Neustadt

Department

Business and Information Technology

Major

Information Science and Technology

Research Advisor

Lea, Bih-Ru

Advisor's Department

Business and Information Technology

Funding Source

Opportunities for Undergraduate Research Experiences (OURE); Eastman Chemical; Center for Enterprise Resource Planning; Software grants from SAP

Abstract

As new discoveries of Autism Spectrum Disorder (ASD) become prevalent, a need for faster and more efficient diagnosis is essential. Results from my 2015-2016 OURE project suggest that color and high dimensional graphs have a large impact on data retention of genetic data and helps in the discovery of important information hidden within the data. My proposed project will develop an interactive visualization software prototype for Autism Spectrum Syndrome (ASD) genetic research data based on literature review and experiment design from my 2015-2016 OURE project. My research will focus on educating people of different backgrounds (age, gender, race, etc.) on the genetic factors that have a direct influence on ASD through the roles of color and high dimensional graphs, particularly the chromosome locations of effected genes. I have collected and organized genetic data taken from SFARI Base and NDAR for my OURE research project that can be used to develop the proposed interactive visualization decision dashboard to conduct survey prototyping, analyze results and make recommendations. The proposed research will develop multiple high dimensional visualization models to allow effective and efficient ASD diagnosis. It is expected that results and prototypes from the proposed will contribute to the process that doctors and physicians diagnose autism, making for more efficient and earlier diagnosis.

Biography

Ever since Scott started school at Missouri S&T, he has been exceling at both academic and extracurricular activities. On top of doing his 2015-2016 OURE project, he works for the Center for Enterprise Resource Planning (ERP), New Student Programs, and is Safety Officer for the concrete canoe design team. He strives to make a lasting impact on his peers. Scott’s hard work and dedication are proven through the results of his research projects.

Presentation Type

OURE Fellows Proposal Oral Applicant

Document Type

Presentation

Award

2016-2017 OURE Fellows recipient

Location

Turner Room

Presentation Date

11 Apr 2016, 3:20 pm - 3:40 pm

This document is currently not available here.

Share

COinS
 
Apr 11th, 3:20 PM Apr 11th, 3:40 PM

Visualizing Genetic Influence on Autism Spectrum Disorder (ASD) Diagnosis: The Roles of Colors and High Dimensional Graphs

Turner Room

As new discoveries of Autism Spectrum Disorder (ASD) become prevalent, a need for faster and more efficient diagnosis is essential. Results from my 2015-2016 OURE project suggest that color and high dimensional graphs have a large impact on data retention of genetic data and helps in the discovery of important information hidden within the data. My proposed project will develop an interactive visualization software prototype for Autism Spectrum Syndrome (ASD) genetic research data based on literature review and experiment design from my 2015-2016 OURE project. My research will focus on educating people of different backgrounds (age, gender, race, etc.) on the genetic factors that have a direct influence on ASD through the roles of color and high dimensional graphs, particularly the chromosome locations of effected genes. I have collected and organized genetic data taken from SFARI Base and NDAR for my OURE research project that can be used to develop the proposed interactive visualization decision dashboard to conduct survey prototyping, analyze results and make recommendations. The proposed research will develop multiple high dimensional visualization models to allow effective and efficient ASD diagnosis. It is expected that results and prototypes from the proposed will contribute to the process that doctors and physicians diagnose autism, making for more efficient and earlier diagnosis.