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2022 Mizzou Faculty Alumni Awards – Notable Presence from MUIDSI
The 67th Annual Faculty Alumni Awardees were announced on July 20, 2022. Dr. Chi-Ren Shyu, MU IDSI Director; Dr. Lori Popejoy, MU IDSI Core Faculty and Interim Dean of Sinclair School of Nursing; and Dr. Dr. Stevan Whitt, Senior Associate Dean for Clinical Affairs of Medicine and MU IDSI’s long term physician collaborator, were among the
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Dr. Blake Meyers Elected to the National Academy of Sciences
Dr. Blake Meyers, MUIDSI Informatics PhD program Core Faculty and Professor in the Division of Plant Science and Technology, and jointly appointed as a Principal Investigator and Member of the Donald Danforth Plant Science Center, has been elected as a Member of the US National Academy of Sciences. https://www.danforthcenter.org/news/blake-meyers-elected-to-national-academy-of-sciences/
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DeepVariant – TrioTrain: Developing a transfer learning protocol using non-human genomes
Presenter:Jenna Kalleberg
Date:12-01-2022
Time:3:30PM-4:00PM
Location:2501 Student Center
Genomic data are widely available for investigating phenotypes that impact both human and animal health. Although the investigation of human health often begins with model organisms, genomics technologies and software are often initially developed with only the human genome in mind, severely limiting their comparative applicability. Translational research requires robust systems-focused, or “One Health,” solutions
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MUIDSI DISSERTATION DEFENSE – ACCELERATING DATA-DRIVEN DISCOVERY IN TYPE 1 DIABETES: AN INFORMATICS-BASED APPROACH
Presenter:Erin Tallon
Date:12-02-2022
Time:3:00PM-4:00PM
Location:Zoom
Type 1 diabetes (T1D) is a lifelong chronic disease characterized by the absolute or near-absolute loss of insulin. For affected individuals, management of T1D is an unremitting challenge that involves constant blood glucose monitoring and lifelong administration and titration of exogeneous insulin. Unfortunately, findings from decades of research have not yet comprehensively translated into substantially
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A combined AI approach to biomedical data analysis: Knowledge representation reasoning, machine learning and explainable AI
Presenter:Satya S. Sahoo, PhD, FAMIA
Date:11-17-2022
Time:3:30pm-4:30pm
Location:Zoom
In this talk, I will explore if and how two traditionally distinct fields of AI, that is, ontology engineering and machine learning can be combined to improve performance outcomes. Using real world examples from epilepsy neurological disorder, the talk will demonstrate the use of biomedical ontologies in machine learning workflows to address the critical challenge of feature engineering in
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