The document summarizes a bioinformatics summer camp, including: 1. The camp will cover basic molecular biology and bioinformatics topics like DNA, proteins, gene expression and the genetic code. 2. Students will work on computational analysis projects involving whole genome sequencing, gene expression profiling, and functional and comparative genomics. 3. The camp will teach techniques for analyzing protein structures and interactions, gene expression data, and identifying pockets on protein surfaces.

1. Bioinformatics Bioengineering Summer Camp June 2001 Yaron Turpaz, Andrew Binkowski, Jie Liang

2. Introduction Basic molecular biology. What is Bioinformatics UIC’s Bioinformatics group Research projects Summer camp research project. Outline http://gila.engr.uic.edu/bioinformatics/

3. DNA Protein Nucleotides sequence Gene expression = Protein production

4. Exons & Introns STOP F R L

5. Biological Diversity Bacteria Fruit Fly Human Yeast

6. The Genetic Code From DNA sequence to Protein sequence. 20 Building blocks of a protein = 20 Amino acids.

7. From protein sequence to Structure APRKFFVGGNWKMNGDKKSLGELIHTLNGAKLSADTEVVCGAPSIYLDFARQKLDAKIGVAAQNCYKVPKGAFTGEISPAMIKDIGAAWVILGHSERRHVFGESDELIGQKVAHALAEGLGVIACIGEKLDEREAGITEKVVFEQTKAIADNVKDWSKVVLAYEPVWAIGTGKTATPQQAQEVHEKLRGWLKSHVSDAVAQSTRIIYGGSVTGGNCKELASQHDVDGFLVGGASLKPEFVDIINAKH =

8. Computational analysis of high-throughput biological data Whole genome sequencing. Global genomic expression & profiling. Functional genomics. Structural genomics/proteomics Comparative genomics. Bioinformatics http://gila.engr.uic.edu/bioinformatics/

9. Interdisciplinary approach Computer science, Mathematics & Statistics. Molecular biology, Biochemistry & Medicine. Rapid growing impact area of BioE: Boston U, UCBerkeley, UCSD, Rice, WashU, MIT,.. Bioinformatics in BioE http://gila.engr.uic.edu/bioinformatics/

10. Structural genomics/proteomics Structural basis of functional motifs in protein families. The CAST server - http://cast.engr.uic.edu/ Drug discovery. Functional genomics Collaboration with TIGR - http://www.tigr.org/ Data mining of microbial DNA sequences for detection of foreign DNA. Whole genome comparative studies. Gene expression analysis Collaboration with cancer biologist (Dr. Westbrook, School of Medicine)‏ Molecular based informatics method to facilitate diagnosis of cancer. Research

11. Gene expression Computational analysis of cDNA microarray expression profiles ~26,000 genes in one experiment

12. Functional correlation in clusters 1. Cell division 2. cell signaling/cell communication 3. cell structure/motility 4. cell/organism defense 5. gene/protein expression 6. metabolism 7. unclassified Genes with similar expression patterns may participate in the same pathway or may be co-regulated. Clustering of expression patterns may reveal such relationships.

13. How Proteins Interfaces with Other Molecules Analysis of protein topographic surfaces: Identify protein function. Predicting binding specificity and affinity. Discovery of functional similarity. Protein interaction with cosolvents Stabilization of protein solution for longer shelf life. Molecular mechanism and optimization. Research – structure & function

14. Atlas of Topographic Surfaces of All Known Protein Structures Automatic identification of binding pockets. Measurement size of surface binding pockets. Drug Discovery Quantifying ligand accessibility. Constructing precise negative imprint or cast of binding site. Structural genomics/proteomics

15. Voronoi Diagram and Delaunay Triangulation Geometry based approach for functional motifs Discrete Flow

16. 3D alpha shapes (HIV-1 protease)‏

17. What is an algorithm? Precisely defined procedure for accomplishing a task. driving directions, furniture assembly instructions, computer programs. Built in hardware: fast Built in software

18. Are computers fast enough? NP-complete problems: eg. Traveling salesman problem : 20 cities a few seconds 30 cities a few hours 60 cities a few decades Computer speed does not increase exponentially.

19. Pockets in Ribonuclease A

20. A Server for Identification of Protein Pockets & Cavities CASTp http://cast.engr.uic.edu/ Users of CASTp: Columbia, Harvard, Mayo Clinic, Princeton, Stanford, U Penn, SUNY Stony Brook, Texas A&M, UCIrvine, UBC, Virginia Tech, Yale, Abbott Lab, Pfizer, SmithKline Beecham, ... Agouron, Emisphere, Vertex, ... Kyoto U, Cambridge, European Molecular Biology Lab, INRA (France), Pasteur-Lille, Uppsala, Weizman,... Brazil, Czech, Korea, Turkey, ...

21. CASTp Results Calculations: Identifies all pockets and cavities. Measures the volume and area analytically. The number, area, and circumcircles of the mouth openings for each pocket. Files via email: pocket and mouth information file, Pocket and mouth atoms, a script file for visualization using rasmol. http://cast.engr.uic.edu/

22. THANK YOU