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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

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

Published On: 11-14-2022 | Published In: Dissertation Defense, Event, Featured News, Speakers and Events,

Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients’ heterogeneity, immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches. However, approximately 50% of cancer patients that are eligible for treatment with ICIs will not respond well, which motivates the exploration of immunotherapy in combination with either targeted treatments

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MUIDSI DISSERTATION DEFENSE: Explainable Artificial Intelligence To Stratify Pan-Cancer Patients For Immune Checkpoint Inhibitor Decision Making
MUIDSI DISSERTATION DEFENSE: Explainable Artificial Intelligence To Stratify Pan-Cancer Patients For Immune Checkpoint Inhibitor Decision Making

Published On: 09-06-2022 | Published In: Dissertation Defense, Event, Featured News, Speakers and Events,

Immune checkpoints are a normal part of the immune system. It engages when proteins on the surface of immune cells called T cells recognize and bind to partner proteins on other cells, such as some tumor cells. Immune based therapies such as ICIs work by blocking checkpoint proteins from binding with their partner proteins. This

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Featured Events

Seminar Series

<em>Identification of Spatially Variable Genes</em>
Identification of Spatially Variable Genes
Presenter:

Jinpu Li

Date:

01-26-2023

Time:

4:00PM-4:30PM

Location:

S203 Memorial Union

<em>Modeling Pyrus calleryana spread in central Missouri using remote sensing and a non-parametric modeling approach</em>
Modeling Pyrus calleryana spread in central Missouri using remote sensing and a non-parametric modeling approach
Presenter:

Justin Krohn

Date:

01-26-2023

Time:

3:30PM-4:00PM

Location:

S203 Memorial Union

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
Presenter:

Erin Tallon

Date:

12-02-2022

Time:

3:00PM-4:00PM

Location:

Zoom

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
Presenter:

Olha Kholod

Date:

11-17-2022

Time:

1:00PM-2:00PM

Location:

Zoom

 

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.