Welcome to 458 Bioinformatics Fall 2010

1. Welcome to 458 BioinformaticsFall 2010 • Times: (1:30 PM R) • Instructors: Wayne Smith Stuart Gordon • Richardon129 Lassiter 102 X8194 X8405 • wasmith@presby.edusggordon@presby.edu

2. Course Homepage: http://web.presby.edu/~wasmith/newcourses/458bioinformatics/

3. Evaluation • Paper Discussions 10% • Participation 10% • Midterm Exam 20% • Project Phase One 15% • Project Phase Two 15% • Project Presentation (part of final) 5% • Final Exam 20%

4. Why Bioinformatics? First off: What is bioinformatics? Bioinformatics arises from the interaction of biology, computer science, math, and statistics. It deals with the staggering amount of biological information, mainly in the form of DNA and protein sequences, and tries to find ways to organize, sort, compare, and decode these sequences to find underlying similarities and patterns that are biologically relevant.

7. Right time, Right place October 2011, 11003 projects

8. “The generation of genomic data will have [has had!] little value without corresponding phenotypic information about individuals' observable characteristics, and computational tools for linking the two.” Craig Venter • “The consequences for clinical medicine, however, have thus far been modest.” Francis Collins

9. It is Sequenced, What’s Next? • Tracing Phylogeny • Finding family relationships between species by tracking similarities between species. • Gene Annotation (cooperative genomics) • Comparison of similar species. • Determining Regulatory Networks • The variables that determine how the body reacts to certain stimuli. • Proteomics • From DNA sequence to a folded protein.

10. Figure 4. The change in misannotation over time in the NR database for the 37 families investigated. Schnoes AM, Brown SD, Dodevski I, Babbitt PC (2009) Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies. PLoSComputBiol 5(12): e1000605. doi:10.1371/journal.pcbi.1000605 http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000605

11. Modeling • Modeling biological processes tells us if we understand a given process • Because of the large number of variables that exist in biological problems, powerful computers are needed to analyze certain biological questions

12. Protein Modeling • Quantum chemistry imaging algorithms of active sites allow us to view possible bonding and reaction mechanisms • Homologous protein modeling is a comparative proteomic approach to determining an unknown protein’s tertiary structure • Predictive tertiary folding algorithms are a long way off, but we can predict secondary structure with ~80% accuracy. The most accurate online prediction tools: PSIPred PHD

13. Regulatory Network Modeling • Micro array experiments allow us to compare differences in expression for two different states • Algorithms for clustering groups of gene expression help point out possible regulatory networks • Other algorithms perform statistical analysis to improve signal to noise contrast

14. Systems Biology Modeling • Predictions of whole cell interactions. • Organelle processes, expression modeling • Currently feasible for specific processes (eg. Metabolism in E. coli, simple cells) Flux Balance Analysis

15. The future… • Bioinformatics is still in it’s infancy • Much is still to be learned about how proteins can manipulate a sequence of base pairs in such a peculiar way that results in a fully functional organism. • How can we then use this information to benefit humanity without abusing it?