Statistical Methods in Computational Biology
Instructor: Jingyi Jessica Li (jli AT stat.ucla.edu)
Dates: 04/01/2014-06/05/2014
Time and Location:Tue & Thr, 12:30-1:45 PM, MS 5225
Lecture Notes
- Lecture 1: Introduction and Data
- Lecture 2: Gene Expression Analysis
- Lecture 3: Multiple Testing Issues; k-means Clustering
- Lecture 4: k-medoids Clustering; Hierarchical Clustering; How to Choose k?
- Lecture 5: Gap Statistic; Liquid Association
- Lecture 6: Alternative Splicing; Multivariate Analysis of Transcript Splicing (MATS)
- Lecture 7: Statistical Inferences for Isoform Expression in RNA-Seq
- Lecture 8: Expectation-Maximization Algorithm
- Lecture 9: Measure of Correlation & Dependence
- Lecture 10: Simulation Methods
- Lecture 11: Markov Chain Monte Carlo; An Ising Model Example
- Lecture 12: Hidden Markov Model
- Lecture 13: Basics of Information Theory
Survey Papers
- Kai Fu: Current Methods in the Analysis of CLIP-Seq Data
- Alden Huang: A Brief Survey of ChIP-seq Protocols and Peak Detection Methods
- Ruyi Huang and Arturo Ramirez: Feature Selection Using Classification Methods
- Arthur Jaroszewicz and Megan Roytman: Statistical Measures of Distance
- Chelsea Jui-Ting Ju: An Overview of Gene Set Enrichment Analysis
- Wanlu Liu and Austin Quach: Statistic Models in Biological Network Analysis
- Medha Uppala: A Survey of Statistical Models to Infer Consensus 3D Chromosomal Structure from Hi-C data
- Yida Zhang and Le Shu: A General Review on Time-series Gene Expression Data