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Established in 2020, POSTECH Mathematical Institute for Data Science (MINDS) is the community of researchers in the areas of fundamental data science, machine learning, artificial intelligence, scientific computing, and humanitarian data science. MINDS mission is to provide a platform for collaboration among researchers and to provide various opportunities for students in data science. MINDS also aims to use our data science research to serve our local and global communities pursuing humanitarian data science.

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3nd POSTECH&Peking SIAM Student Chapter Joint Conference 2023.11.01

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[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]-상시모집 2023.07.25

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고] 2023.07.14

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구교수 채용 공고] 2023.06.12

Seminar | Joint seminar for probability and mathematical biology 2023.05.02

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고] 2023.02.15

Upcoming Events

Schedule

MINDS SEMINAR

MINDS Seminar Series | Hong Hee Won (Sungkyunkwan University) - GWAS and Mendelian randomization in medicine

MINDS SEMINAR

period : 2022-04-12 ~ 2022-04-12

time : 17:00:00 ~ 18:00

개최 장소 : Online streaming (Zoom)

Topic : GWAS and Mendelian randomization in medicine

개요

Date	2022-04-12 ~ 2022-04-12	Time	17:00:00 ~ 18:00
Speaker	Hong Hee Won	Affiliation	Sungkyunkwan University
Place	Online streaming (Zoom)	Streaming link	ID : 688 896 1076 / PW : 54321
Topic	GWAS and Mendelian randomization in medicine
Contents	Observational studies are useful to identify associations between risk factors and diseases, but often show inconsistent results due to heterogeneity among studies such as metrics, race, and cohort characteristics. In addition, many associated factors have a bidirectional interaction with the disease. For example, although the risk of disease is increased by an associated factor, it can be also increased due to the occurrence of the disease. In the case of such a complex epidemiologic relationship, it is difficult to confirm the exact causality or direction of interaction only by observational studies. The concept of causality is important in medicine because it enables proper and effective treatments. Randomized controlled trials (RCTs) is considered a gold standard to confirm a causal relationship between risk factors and disease. For example, in interventional studies such as drug studies, causality can be confirmed through RCT. In many cases such as smoking and lung cancer, however, RCTs are not feasible because it is unethical to induce risk factors through intervention. The Mendelian randomized study (MR) is based on a fact that genetic variants which increase or decrease the risk of a factor are randomly assigned during meiosis. Comparing the difference in the risk of disease for two groups that have high or low genetic risk for the factor can evaluate whether the factor induces the disease without intervention. In this presentation, I will talk about genome-wide associations studies that identify genetic variants associated with traits such as risk factors and diseases. Then, I will explain MR analyses, assumptions, interpretation as well as several examples from literature.