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Introduction to Bioinformatics

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jaclyn
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Introduction to Bioinformatics. Burkhard Morgenstern Institute of Microbiology and Genetics Department of Bioinformatics Goldschmidtstr. 1 G ö ttingen, March 2004. Introduction to Bioinformatics. Bioinformatics in G ö ttingen: Dep. of Bioinformatics (UKG), Edgar Wingender

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Introduction to Bioinformatics
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  1. Introduction to Bioinformatics Burkhard Morgenstern Institute of Microbiology and Genetics Department of Bioinformatics Goldschmidtstr. 1 Göttingen, March 2004

  2. Introduction to Bioinformatics Bioinformatics in Göttingen: • Dep. of Bioinformatics (UKG), Edgar Wingender • Dep. of Bioinformatics (IMG), BM • Inst. Num. and Applied Mathematics, Stephan Waack • Dep. of Genetics (Hans Fritz, IMG), Rainer Merkl

  3. Introduction to Bioinformatics Definition: Bioinformatics = development and application of software tools for Molecular Biology

  4. Bioinformatics: Topics: • Sequence Analysis (Gene finding …) • Structure Analysis (RNA, Protein) • Gene Expression Analysis • Metabolic Pathways, Virtual Cell

  5. Bioinformatics: Areas of work: • Application of software tools for data analysis in (Molecular) Biology • Computing infrastructure, database development, support • Development of algorithms and software tools

  6. Information flow in the cell

  7. Information flow in the cell Idea: Sequence -> Structure -> Function

  8. Information flow in the cell • Lots of data available at the sequence level • Fewer data at the structure and function level

  9. Topics of lecture: • Data bases SwissProt, GenBank • Pair-wise sequence comparison • Data base searching • Multiple sequence alignment • Gene prediction

  10. Protein data bases • Sanger and Tuppy: protein-sequencing methods (1951) • Margaret Dayhoff: Atlas of Protein Sequence and Structure (1972); later: Protein Identification Resource (PIR) as international collaboration (a) Organize proteins into families; (b) Amino acid substitution frequencies • Amos Bairoch: SwissProt (1986)

  11. Exponential growth of data bases

  12. DNA data bases • Maxam and Gilbert; Sanger: DNA sequencing methods (1977) • GenBank DNA data base (1979), now run by NCBI. • Collaboration with EMBL (1982), DDBJ (1984) • Translated DNA sequences stored in protein data bases (PIR, trEMBL)

  13. Most important tool for sequence analysis: • Sequence comparison

  14. The dot plot Y Q EW T Y I V A R E A Q Y E C I V M R E Q Y

  15. The dot plot Y Q EW T Y I V A R E A Q Y E C I V M R E Q Y

  16. The dot plot Y Q EW T Y I V A R E A Q Y E C I X V X M R X E X X X Q X X Y X X

  17. The dot plot Y Q EW T Y I V A R E A Q Y E C IX VX M R X E X X X Q X X Y X X

  18. The dot plot Y Q EW T Y I VA R E A Q Y E C IX VX M RX EX X X QX X YX X

  19. The dot plot Y Q EW T Y I V A R E A Q Y E C I X V X M R X EX X X QX X YX X

  20. The dot plot Y Q EW T Y Q E V R E Y Q E I C I X V X M R Y X X X Q X X X E X X X X

  21. The dot plot Y Q EW T Y Q E V R E Y Q E I C I X V X M R YX X X QX X X E X X X X

  22. The dot plot Advantages: • Various types of similarity detectable (repeats, inversions) • Useful for large-scale analysis

  23. The dot plot

  24. Pair-wise sequence alignment Evolutionary or structurally related sequences: • alignment possible Sequence homologies represented by inserting gaps

  25. Pair-wise sequence alignment T Y I V A R E A Q Y E C I X V X M R X E X X Q X Y X X

  26. Pair-wise sequence alignment T Y I V A R E A Q Y E C IX VX M RX E X X Q X YX X

  27. Pair-wise sequence alignment T Y I V A R E A Q Y E C IX VX M RX E X X Q X YX X

  28. Pair-wise sequence alignment T Y I V A R E A Q Y E C IX VX M RX E X X Q X YX X

  29. Pair-wise sequence alignment T Y I VAR EAQ Y E C I VMR E Q Y

  30. Pair-wise sequence alignment T Y I VAR EAQ Y E - C I VMR E - Q Y –

  31. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Global alignment: sequences aligned over the entire length

  32. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Basic task: Find best alignment of two sequences

  33. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Basic task: Find best alignment of two sequences = alignment that reflects structural and evolutionary relations

  34. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Questions: • What is a good alignment? • How to find the best alignment?

  35. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Problem: • Astronomical number of possible alignments

  36. Pair-wise sequence alignment T Y I V A R E A Q Y E C I - V M R E - Q Y – Problem: • Astronomical number of possible alignments

  37. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – Problem: • Astronomical number of possible alignments • Stupid computer has to find out: which alignment is best ??

  38. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – First (simplified) rules: • Minimize number of mismatches • Maximize number of matches

  39. Pair-wise sequence alignment T Y I V A R E A Q Y E C I - V M R E - Q Y – First (simplified) rules: • Minimize number of mismatches • Maximize number of matches

  40. Pair-wise sequence alignment T Y I V A R E A Q Y E - C I V M R E - Q Y – First (simplified) rules: • Minimize number of mismatches • Maximize number of matches