Topics in Biomedical Data Science: Large-scale inference
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Course Description
The recent explosion of data generated in the fields of biology and medicine has led to many analytical challenges and opportunities for understanding human health. This graduate-level course focuses on methodology for large-scale inference from biomedical data. Topics include one-dimensional and multidimensional probability distributions; hypothesis testing and model comparison; statistical modeling; and prediction. This course will place a special emphasis on applications of these approaches to i) human genetic data; ii) hospital in-patient and health questionnaire data, which is increasingly available with the emergence of large precision initiatives like the UK Biobank and Precision Medicine Initiative; and iii) wearable and social network data.
Grading Basis
MOP - Medical Option (Med-Ltr-CR/NC)
Min
2
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Programs
BIODS215
is a
completion requirement
for: