Biological exploration on genetic expression and protein synthesis in living organisms is used to discover causal and interactive relationships in biological processes. Current GeneChip microarray technology provides a platform to an- alyze up to 500,000 molecular reactions on a single chip, providing thousands of genetic and protein expression results per test. Using visualization tools and priori knowledge of genetic and protein interactions, visual networks are used to model and analyze the results. The virtual reality environment designed and implemented for this project provides visualization and data modeling tools commonly used in genetic ex- pression data analysis. The software processes normalized genetic profile data from microarray testing results and association information from protein-to- protein databases. The data is modeled using a network of nodes to represent data points and edges to show relationships. This information is visualized in virtual reality and modeled using force directed networking algorithms in a fully explorable environment.
","abstract_html":"<p>Biological exploration on genetic expression and protein synthesis in living organisms is used to discover causal and interactive relationships in biological processes. Current GeneChip microarray technology provides a platform to an- alyze up to 500,000 molecular reactions on a single chip, providing thousands of genetic and protein expression results per test. Using visualization tools and priori knowledge of genetic and protein interactions, visual networks are used to model and analyze the results. The virtual reality environment designed and implemented for this project provides visualization and data modeling tools commonly used in genetic ex- pression data analysis. The software processes normalized genetic profile data from microarray testing results and association information from protein-to- protein databases. The data is modeled using a network of nodes to represent data points and edges to show relationships. This information is visualized in virtual reality and modeled using force directed networking algorithms in a fully explorable environment.</p>","abstract_has_math":false,"creators":["Cotes, Joshua"],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-01-01T08:00:00Z","date_published":"2017-01-01T08:00:00Z","updated_at":"2026-07-24T02:13:29Z","subjects":["Computer Sciences"],"languages":[],"rights":["Access is available to all users"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/441","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Cotes, Joshua"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access is available to all users"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/441"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Biological exploration on genetic expression and protein synthesis in living organisms is used to discover causal and interactive relationships in biological processes. Current GeneChip microarray technology provides a platform to an- alyze up to 500,000 molecular reactions on a single chip, providing thousands of genetic and protein expression results per test. Using visualization tools and priori knowledge of genetic and protein interactions, visual networks are used to model and analyze the results. The virtual reality environment designed and implemented for this project provides visualization and data modeling tools commonly used in genetic ex- pression data analysis. The software processes normalized genetic profile data from microarray testing results and association information from protein-to- protein databases. The data is modeled using a network of nodes to represent data points and edges to show relationships. This information is visualized in virtual reality and modeled using force directed networking algorithms in a fully explorable environment.
"]},{"key":"dc:title","label":"Title","values":["Gene expression prospective simulation and analysis unsing data mining and immersive virtual reality visualization"]}]}],"canonical_facts":{"dc:creator":["Cotes, Joshua"],"dc:description.abstract":["Biological exploration on genetic expression and protein synthesis in living organisms is used to discover causal and interactive relationships in biological processes. Current GeneChip microarray technology provides a platform to an- alyze up to 500,000 molecular reactions on a single chip, providing thousands of genetic and protein expression results per test. Using visualization tools and priori knowledge of genetic and protein interactions, visual networks are used to model and analyze the results. The virtual reality environment designed and implemented for this project provides visualization and data modeling tools commonly used in genetic ex- pression data analysis. The software processes normalized genetic profile data from microarray testing results and association information from protein-to- protein databases. The data is modeled using a network of nodes to represent data points and edges to show relationships. This information is visualized in virtual reality and modeled using force directed networking algorithms in a fully explorable environment.
"],"dc:identifier":["https://dc.ewu.edu/theses/441"],"dc:rights":["Access is available to all users"],"dc:subject":["Computer Sciences"],"dc:title":["Gene expression prospective simulation and analysis unsing data mining and immersive virtual reality visualization"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:13:29Z"}