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MU Institute for Data Science and Informatics

Established in 2008, MUIDSI has led the way in cutting edge informatics research and education.

Featured News

NGA Ge0-Hack for Humanity Student Team Wins 2nd Place

NGA Ge0-Hack for Humanity Student Team Wins 2nd Place

The National Geospatial-Intelligence Agency (NGA) and T-REX sponsored the NGA Geo-Hack for Humanity held at the T-REX center in downtown St….

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Data Science Innovation to Advance Journalism 

Data Science Innovation to Advance Journalism 

COLUMBIA, Mo. (July 24, 2023) — Damon Kiesow is now the Knight Chair in Journalism Innovation at the Missouri…

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Featured Events

Seminar Series

Evaluating Benchmark Models with Multi-Omics Approaches for Long-Term Survival (LTS) Prediction Across 23 Cancer Studies

Evaluating Benchmark Models with Multi-Omics Approaches for Long-Term Survival (LTS) Prediction Across 23 Cancer Studies

Cancer is a major cause of global mortality, necessitating accurate long-term survival (LTS) predictions for patients to optimize treatment…

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Prototyping a Web-based Interface of Sensor Technologies for Remote Care Coordination and Self-management

Prototyping a Web-based Interface of Sensor Technologies for Remote Care Coordination and Self-management

The widespread adoption of consumer sensor technologies, including wearable and in-home sensors, present an opportunity for ambient monitoring of…

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Speakers and Events

MUIDSI DISSERTATION DEFENSE – ACCELERATING DATA-DRIVEN DISCOVERY IN TYPE 1 DIABETES: AN INFORMATICS-BASED APPROACH

MUIDSI DISSERTATION DEFENSE – ACCELERATING DATA-DRIVEN DISCOVERY IN TYPE 1 DIABETES: AN INFORMATICS-BASED APPROACH

Type 1 diabetes (T1D) is a lifelong chronic disease characterized by the absolute or near-absolute loss of insulin. For…

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MUIDSI Dissertation Defense: IDENTIFICATION OF IMMUNE-RELATED GENE SIGNATURES TO EVALUATE IMMUNOTHARAPEUTIC RESPONSE IN CANCER PATIENTS USING EXPLORATORY SUBGROUP DISCOVERY

MUIDSI Dissertation Defense: IDENTIFICATION OF IMMUNE-RELATED GENE SIGNATURES TO EVALUATE IMMUNOTHARAPEUTIC RESPONSE IN CANCER PATIENTS USING EXPLORATORY SUBGROUP DISCOVERY

Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients’ heterogeneity, immune checkpoint inhibitors (ICIs) represent…

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MU Institute for Data Science and Informatics (MU IDSI) launched a 5-year plan for Data-Driven Discovery research in four areas using emerging data science and informatics methods and technologies:

  1. Data-Driven Precision Medicine
  2. Data-Driven Agriculture
  3. Data-Driven Social and Behavioral Science
  4. Data-Driven Precision Rural and Population Health

Activities include journal clubs, colloquium series, ideas labs, and team building.