CS 6293 Advanced Topics: Bioinformatics

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4/11: Final homework

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Overview | Prerequisite | Time and Location | Instructor | Textbooks and Resources | Policies | Lecture Schedule and Slides

Overview

This course provides a review of both old and new challenging problems in the area of bioinformatics and computational biology. The course does not assume prior background in biology. However you do need to have a strong background in algorithms and probability/statistics (see prerequisite).

We will first cover some basics in biology, and then spend about 1/3 of the semester reviewing some traditional topics in bioinformatics (which overlaps with many topics covered in CS5263 and CS6293 in previous semesters). For the remaining semester we will be mainly focusing on Translational Bioinformatics. A majority of the materials will be coming from PLoS Computational Biology: Translational Bioinformatics Collection. Additional topics may be covered depending on interest level.

Prerequisite

The official prerequisite for the course is CS5263. If you do not meet the prerequisite but are interested in participating in this course, you are expected to have taken the graduate algorithms course and recevied a grade of B or better. You are also expected to have a solid knowledge of probability and statistics, and a strong desire to learn by yourself. If you do not meet the above mentioned criteria, please talk to me at the beginning of this course.

Time and Location

We meet in room MB 1.1.03 . Lecturers are Tuesday and Thursday, 4:00-5:15 PM.

Instructor

Dr. Jianhua Ruan
Office location: FLN 4.01.48
Office hours: Wednesday 2:00-3:00pm, or by appointment
Email: jianhua.ruan@utsa.edu
Phone: (210) 458-6819

Textbooks and Resources

There is no textbook required for this course. The instructor will provide the needed materials including chapters from textbooks, journal papers, and review articles in class or on course homepage.

Online Reading Materials and Resources

Grading Policy

At most 3 classes missed without affecting grade, unless approved by the instructor.
Late assignments will not be accepted and a score of zero will be given

Collaboration Policy

Lecture Schedule and Slides

Week 1 (Jan 14, 16): Introduction to molecular biology

Week 2 (Jan 21, 23): Sequence alignment

Week 3 (Jan 28, 30): String matching and short-read mapping

Week 4-5 (Feb 4, 6, 11, 13): Gene expression data analysis

Week 6 (Feb 18, 20): Biological networks

Week 7 - 15: Translational Bioinformatics

           
  2/25 T Chapter 2: Data-Driven View of Disease Biology Jianhua Ruan Slides Additional reading: Statistics and Probability Primer
  2/27 R Chapter 4: Protein Interactions and Disease Md. Jamiul Jahid Slides  
  3/4 T Chapter 5: Network Biology Approach to Complex Diseases
Lu Liu Slides  
  3/6 R Chapter 3: Small Molecules and Disease
CheWei Chen Slides  
    Spring Break      
  3/18 T Chapter 7: Pharmacogenomics
K.M. Rahman Slides  
  3/20 R Chapter 8: Biological Knowledge Assembly and Interpretation
Zhen Gao Slides  
  3/25 T Chapter 6: Structural Variation and Medical Genomics
Nesthor-Omer Perez-Cruz Slides  
  3/27 R Chapter 14: Cancer Genome Analysis Hung-I Chen Slides  
  4/1 T Chapter 15: Disease Gene Prioritization
Qian Huang Slides  
  4/3 R Chapter 9: Analyses Using Disease Ontologies
Mohand Guiddir Slides  
  4/8 T Chapter 12: Human Microbiome Analysis
Omer Aslan Slides  
  4/10 R David, GSEA, and EnrichNet Jianhua Ruan &
Lu Liu

GSEA

EnrichNet

 
  4/15 T Chapter 17: Bioimage Informatics for Systems Pharmacology
Iffat Chowdhury Slides  
  4/17 R Chapter 13: Mining Electronic Health Records in the Genomics Era
Deepti Marimadaiah Slides  
  4/22 T Chapter 16: Text Mining for Translational Bioinformatics
Turki Alanazi Slides  
  4/24 R Chapter 11: Genome-Wide Association Studies
Jianhua Ruan    
  4/29 T TBD      
           
  5/5 M Final Project Report Due      

 

 

Tentative lecture topics

Topics Number of weeks
Introduction to molecular biology and basic sequence analysis algorithms 2
NGS data processing 1.5
Gene expression, gene ontology and gene set enrichment analysis 1.5
Translational Bioinformatics 7
Other topics 2