Title: Computational Modeling of Molecular Structures - one of Big Bio Data Mining and Modeling Courses (CMP SC 8170)

Location: EBW 240

Time: Mon & Wed, 2:30 - 3:45, 2014 Spring Semester

Instructors: Prof. Jianlin Cheng

Office hours: Mon 4 - 5, EBW 109

Acknowledgement: The course development is supported by a National Science Foundation CAREER award. Some images and figures used in the lectures are provided by images.google.com and other sources.

Syllabus

Lectures

1. Introduction [PDF slides]

2. Principles, Algorithms and Data Strucutres for Template-Based Protein Structure Modeling [PDF slides]

Homework: read the article and write a half page summary (12-point font): A. Sali, T.L. Blundell. Comparative Protein Modeling by Satisfaction of Spatial Restraints. JMB, 1993. (Due on Feb. 3). Email your assignment to mumachinelearning@gmail.com.

3. Principles, Algorithms, and Data Structures for Template-Free Protein Structure Modeling [PDF slides]

Homework: read the article and write a half page summary: K.T. Simmons, et al. Assembly of protein tertiary structures from fragments. JMB. 1997. (Due on Feb. 24.)

4. Principles, Algorithms and Data Structures for Protein Docking [PDF slides]

Homework: read the article and write a half page summary: D. Ritchie. Recent progress and future directions in protein-protein docking. Current Protein and Peptide Science, 2008. (Due on March 17).

5. Principles, Algorithms, and Data Structures for Genome Structure Modeling [PDF]

Homework: read one of the two following articles and write a half page summary: E. Lieberman-Aiden et al. Comprehensive mapping of long-range interactions reveal folding principles of the human genome. Science, 2009; Z. Wang, R. Cao, K. Taylor, A. Briley, C. Caldwell, J. Cheng. The properties of human genome conformation and spatial gene interaction and regulation networks. PLOS ONE. 8(3):e58793.T. Trieu, J. Cheng. Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data. Nucleic Acids Research, 2014. (Due on April 10, Thursday).

6. Principles, Algorithms, and Data Structures for RNA Structure Modeling [PDF Slides]

Projects

This course is focused on developing and benchmarking 3D molecular structure modeling tools and algorithms in order for students to study common principles, representations, sampling algorithms and software engineering in molecular modeling. Students are required to make, implement and assess their plans of developing and testing the following software tools by doing a series of group projects. The discussion and presentation of project plan, implementation and results account for about 2/3 - 3/4 course time, while the lectures use the other 1/4 - 1/3 course time.

Develop a prototype of template-based protein modeling tool

Develop a prototype of template-free protein modeling tool

Benchmark three protein docking tools

Apply a prototype of genome structure modeling tool using a Markov Chain Monte Carlo approach to two data sets (Hi-C contact data of Chr. 7 in Wang et al. (The normalized contact matrix derived from the Hi-C contact data used in Tuan and Cheng, Nucleic Acids Research, 2014), 5C data in Rausseau. (Ref: Rousseau et al. Three-dimensional modeling of chromatin structure from interaction frequency data using Markov chain Monte Carlo sampling. BMC Bioinformatics, 2011. Data sets: (1) Rousseau et al. 2001 (a gene loci); (2) Liberman-Aiden et al. (a chromosome), 2009; (3) Wang et al., 2013 (a chromosome)