1. 1 Algorithms in Computational Biology (236522) Spring 2006 Lecturer: Golan Yona Office hours: Wednesday or Thursday 2-3pm (Taub 632, Tel 4356) TA: Itai Sharon Office hours: Tuesday 2:30-3:20 (Taub 621, Tel 4946) Lecture: Monday 12:30-2:20, Taub 4 Tutorial: Tuesday 1:30-2:20, Taub 7

2. 1 Computational Biology Computational biology is the application of computational tools and techniques to (primarily) molecular biology. It enables new ways of study in life sciences, allowing analytic and predictive methodologies that support and enhance laboratory work. It is a multidisciplinary area of study that combines Biology, Computer Science, and Statistics. Computational biology is also called Bioinformatics, although many practitioners define Bioinformatics somewhat narrower by restricting the field to molecular Biology only.

3. 1 Examples of Areas of Interest Understanding the structure of genomes (detecting genes, regulatory elements, variations) Deciphering structure and function of proteins Discovery of cellular “procedures” (pathways) Indentifying disease-causing genes Building the tree of life More..

4. 1 Exponential growth of biological information: growth of sequences, structures, and literature.

5. 1 Course’s goals The focus of this course is the set of algorithms, tools and models used today to analyse molecular biological data, recover and discover hidden information.

6. 1 Four aspects to any problem Biological –What is the task? Algorithmic –How to perform the task at hand efficiently? Learning –How to adapt/estimate/learn parameters and models describing the task from examples Statistics –How to differentiate true phenomena from artifacts

7. 1 Example: Sequence Comparison Biological – Evolution preserves sequences, thus similar genes might have similar function Algorithmic – Consider all ways to “align” one sequence against another Learning – How do we define “similar” sequences? Use examples to define similarity Statistics – When we compare a query sequence to ~10 6 sequences, what is a random match and what is true one

8. 1 Relations to Other Courses Bioinformatics Software (cs236523). The course Introduction to Bioinformatics covers practical aspects and hands on experience with many web-based bioinformatics programs. Albeit not a formal requirement, it is recommended that you look on the website www.cs.technion.ac.il/~cs236606 and examine the relevant software. Bioinformatics algorithms (cs236522). This is the current course which focuses on modeling some bioinformatics problems and presents algorithms for their solution. Bioinformatics project (cs236524). Developing bioinformatics tools under close guidance. Advanced topics in bioinformatics.

9. 1 Course Prerequisites Computer Science and Probability Background Data structure 1 (cs234218) Algorithms 1 (cs234247) Probability (any course) Or permission from instructor Biology background Formally: none (to allow CS studnets to take this course) Recommended: Molecular Biology 1 (especially for those in the Bioinformatics track), or a similar Biology course, and/or a serious desire to complement your knowledge in Biology by reading the appropriate material (see the course home).

10. 1 Requirements & Grades 40% homework, in five or six assignments. Homework is obligatory. 60% test. Must pass 55 for the homework’s grade to count Exam date: 17.7.06

11. 1 Syllabus Introduction, biological background (0.5 weeks) Gene detection and function prediction –Pairwise alignment (2 weeks) –Multiple sequence alignment (2 weeks) –Profile and Hidden Markov Models (2 weeks) Motif detection (1 week) Phylogenetic trees (2 weeks) Expression data analysis, pathways (2.5 weeks) Protein structure analysis (2 weeks)

12. 1 Bibliography Biological Sequence Analysis, R.Durbin et al., Cambridge University Press, 1998 Introduction to Molecular Biology, J. Setubal, J. Meidanis, PWS publishing Company, 1997 Misc papers Some slides adopted from courses taught by Nir Friedman (Hebrew U), Dan Geiger and Shlomo Moran Course home: webcourse.cs.technion.ac.il/~cs236522

13. 1 Biological Background First home work assignment: Read the first chapter (pages 1- 30) of Setubal et al., 1997. (copies are available in the Taub building library, and in the central library). Answer the questions of the first assignment in the course site.

14. 1 Course starts..

15. 1 Human Genome Most human cells contain 46 chromosomes: 2 sex chromosomes (X,Y): XY – in males. XX – in females. 22 pairs of chromosomes named autosomes.

16. 1 DNA Organization Source: Alberts et al

17. 1 The Double Helix Source: Alberts et al

18. 1 DNA Components Four nucleotide types: Adenine Guanine Cytosine Thymine

19. 1 Base pairs Hydrogen bonds (electrostatic connection): A-T C-G

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21. 1 Genome Sizes E.Coli (bacteria)4.6 x 10 6 bases Yeast (simple fungi)15 x 10 6 bases Smallest human chromosome 50 x 10 6 bases Entire human genome 3 x 10 9 bases

22. 1 Genetic Information Genome – the collection of genetic information. Chromosomes – storage units of genes. Gene – basic unit of genetic information. They determine the inherited characters.

23. 1 Genes The DNA strings include: Coding regions (“genes”) – E. coli has ~4,000 genes – Yeast has ~6,000 genes – C. Elegans has ~13,000 genes – Humans have ~32,000 genes Control regions – These typically are adjacent to the genes – They determine when a gene should be “expressed” “Junk” DNA (unknown function - ~90% of the DNA in human’s chromosomes)

24. 1 The cell All cells of an organism contain the same DNA content (and the same genes) yet there is a variety of cell types.

25. 1 Example: Tissues in Stomach How is this variety encoded and expressed ?

26. 1 Central Dogma Transcription mRNA Translation Protein Gene cells express different subset of the genes In different tissues and under different conditions שעתוק תרגום

27. 1 Central dogma

28. 1 Transcription Coding sequences can be transcribed to RNA RNA –Similar to DNA, slightly different nucleotides: different backbone –Uracil (U) instead of Thymine (T) Source: Mathews & van Holde

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30. 1 Transcription: Junk DNA, RNA Editing, Alternative Splicing Exons hold information, they are more stable during evolution. This process takes place in the nucleus. The mRNA molecules diffuse through the nucleus membrane to the outer cell plasma. 1.Transcribe to RNA 2.Eliminate introns 3.Splice (connect) exons * Alternative splicing exists

31. 1 RNA roles Messenger RNA (mRNA) – Encodes protein sequences. Each three nucleotide acids translate to an amino acid (the protein building block). Transfer RNA (tRNA) – Decodes the mRNA molecules to amino-acids. It connects to the mRNA with one side and holds the appropriate amino acid on its other side. Ribosomal RNA (rRNA) – Part of the ribosome, a machine for translating mRNA to proteins. It catalyzes (like enzymes) the reaction that attaches the hanging amino acid from the tRNA to the amino acid chain being created....

32. 1 Central dogma

33. 1 Proteins Made of 20 Amino acids

34. 1 Translation Translation is mediated by the ribosome Ribosome is a complex of protein & rRNA molecules The ribosome attaches to the mRNA at a translation initiation site Then ribosome moves along the mRNA sequence and in the process constructs a sequence of amino acids (polypeptide) which is released and folds into a protein.

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36. 1 Helper molecules: tRNA

37. 1 The Genetic Code

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41. 1 Protein Structure Proteins are poly- peptides of 70- 3000 amino-acids This structure is (mostly) determined by the sequence of amino-acids that make up the protein

42. 1 Various structures with different functions Structural framework (keratin, collagen) Transport and storage of small molecules (hemoglobin) Transmit information (hormones, receptors) Antibodies Blood clotting factors Enzymes Protein structures

43. 1 Protein-Protein interactions

44. 1 Pathways

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47. 1 Evolution Related organisms have similar DNA –Similarity in sequences of proteins –Similarity in organization of genes along the chromosomes Evolution plays a major role in biology –Many mechanisms are shared across a wide range of organisms –During the course of evolution existing components are adapted for new functions

48. 1 Evolution Evolution of new organisms is driven by Diversity –Different individuals carry different variants of the same basic blue print Mutations –The DNA sequence can be changed due to single base changes, deletion/insertion of DNA segments, etc. Selection bias

49. 1 The Tree of Life Source: Alberts et al