1. Bioinformatics Predrag Radivojac I NDIANA U NIVERSITY

2. Basics of Molecular Biology Can we understand how cells function? Eukaryotic cell

3. Bioinformatics is multidisciplinary! What is Bioinformatics? –Integrates: computer science, statistics, chemistry, physics, and molecular biology –Goal: organize and store huge amounts of biological data and extract knowledge from it Major areas of research –Genomics –Proteomics –Databases Practical discipline Some major applications · Drug design · Evolutionary studies · Genome characterization

4. Interesting Problems Sequence Alignment

5. Interesting Problems

6. Sequence assembly Goal: solve the puzzle, i.e. connect the pieces into one genomic sequence

7. Interesting Problems Proteomics Mass spectrometry

8. Interesting Problems Microarray data

9. Interesting Problems Functional Genomics Gene Regulation

10. Diseases are interconnected… Goh et al. PNAS, 104: 8685 (2007).

11. Disease www.cancer.gov Development of tools that can be used to understand and treat human disease Prediction of disease-associated genes Important from biological standpoint medical standpoint computational standpoint Background human genome low-throughput data high-throughput data ontologies for protein function at multiple levels The Time is Right!

12. Alzheimer’s disease Top PhenoPred hits: 1) CDK5 2) NTN1 AUC = 77.5%

13. Loss/Gain of function and disease Pauling et al. Science 110: 543 (1949). Chui & Dover. Curr Opin Pediatr, 13: 22 (2001). Sickle Cell Disease: Autosomal recessive disorder E6V in HBB causes interaction w/ F85 and L88 Formation of amyloid fibrils Abnormally shaped red blood cells, leads to sickle cell anemia Manifestation of disease vastly different over patients 2hbs E6V http://gingi.uchicago.edu/hbs2.html 4hhb

14. Lipitor (ATORVASTATIN) E6V

15. 15 Proteins = chains of amino acids biomolecule, macromolecule –more than 50% of the dry weight of cells is proteins polymer of amino acids connected into linear chains strings of symbols machinery of life –play central role in the structure and function of cells –regulate and execute many biological functions a) amino acid b) amino acid chain Introduction to Protein Structure by Branden and Tooze

16. 16 peptide bonds are planar and strong by rotating at each amino acid, proteins adopt structure Protein structure Introduction to Protein Structure by Branden and Tooze

17. 17 Protein function Multi-level phenomenon –biochemical function –biological function –phenotypical function Example: kinase –biochemical function – transferase –biological function – cell cycle regulation –phenotypical function – disease Function is everything that happens to or through a protein (Rost et al. 2003)

18. Myoglobin 1.4A X-ray PDB: 2jho 153 residues C  - C  < 6A Protein contact graph

21. 21 S113 of isocitrate dehydrogenase G = (V, E) f: V  A A = {A, C, D, … W, Y} g: V  {  1, +1} Notation: Residue neighborhood

22. 22 Graphlets are small non-isomorphic connected graphs. Different positions of the pivot vertex with respect to the graphlet correspond to graph-theoretical concept of automorphism orbits, or orbits. S Przulj et al. Bioinformatics 20: 3508 (2004).

23. Results

24. 2-graphlets:01 3-graphlets:011, 012 4-graphlets:0111, 0112 0122, 0123 Key insight: Efficient combinatorial enumeration of graphlets / orbits over 7 disjoint cases breadth-first search

25. 0 1 | A | o 2 | A | 2 o 5, o 6, o 11 | A | 3 o 3, o 4 ? A = {0, 1} 00, 01 = 10, 11 (3) A = {0, 1, 2} 00, 11, 22, 01 = 10, 02 = 20, 12 = 21 (6) binomial (multinomial) coefficients | A |= 20, dimensionality = 1,062,420 0101 0202

26. Inner product between vectors of counts of labeled orbits where K is a kernel because matrices of inner products are symmetric and positive definite (proof due to David Haussler). Graphlet kernel  i ( x ) is the number of times labeled orbit i occurs in the graph