Winter 2023, Tuesday / Thursday 10:00-11:30am
Instructor: Sara Mostafavi, PhD.
Teaching Assistants: Xingming Tu, Anna Spiro.
Time and place: Tuesday / Thursday 10:00-11:30am, CSE2 (Gates Build) G01
Office hours:
Prof. Mostafavi, by appointment, please email Sara.
Xinming Tu: Wednesdays at 11am at CSE506. Please email for virtual office hours.
Anna Spiro: Mondays at 9:30am, Allen Center 5th floor breakout room. Please email for virtual office hours.
Discussion Board: Ed
Description: Computational biology brings together recent advances in computational methods, including machine learning, and genomic measurement technologies, to provide insights into how our genomes work and underlie health and disease.
This course will introduce computational and statistical approaches and practices for deriving robust and rigorous insights from modern genomics datasets. Lectures alternate between genomics-inspired problem formulation and foundational statistical and computational approaches for addressing them. In foundational lectures, we will cover basics of statistical inference, hidden confounding factors, deep neural networks. From the genomics side, we will cover the latest research problems in human genetics, regulatory genomics, multi-omic data, and single cell genomics.
See Schedule page for weekly topics
See Syllabus page for the following information:
Topics
Pre-requisites
Student evaluation
Suggested background reading