Introduction to Bioinformatics: CMSC54610-1, Spring quarter 2006.

Lecture 2 Some things I forgot from last time:

• Overview and book review
• Hydrophilicity and Hydrophobicity
• The C-value paradox and increasing interactivity

Chapter 2: Data searches and pairwise alignments

• Dot plots: a visual guide to local alignments
  • The dotmatcher program is explained in this introduction
  • What does it do? Shows where the restricted edit distance is small.
• Edit distance notes
• Distance versus score
• Scoring matrices: BLOSSUM, PAM etc. are often defined by aligning similar sequences
• Dynamic programming to compute the extrema (min distance <==> max score)
  • Global alignment: Needleman-Wunsch
  • Local alignment: Smith-Waterman (omit negative scores)
• Database searches
  • BLAST: find short seeds and grow
  • FASTA: look at differences
• Multiple sequence alignments
• Homework problems:
  • (2.1) From the book: Chapter 2, problem 2.5: give at least two optimal alignements for this sequence (see the solution at the back of the book for support, but you still need to find all the arrows!)
  • (2.2) From the book: Chapter 2, problem 2.6
  • (2.3) use dotmatcher to examine the alignment of the sequences in the handout:
    • AATTGCCGCCGTCGTTTTCAGCAGTTATGTCAGATC
    • TCCCAGTTATGTCAGGGGACACGAGCATGCAGAGAC
    Try different window sizes and `threshold' values to see what shows the local alignment best. Explain your reasoning and include plots to back up your claims. You should exhibit at least two areas of local alignment of six or more. Label your plots so it is clear which sequence is on which axis. Also label the major local alignments that emerge in the plots.
  • Homework is due by the beginning of the next class.
    • Preferred: Homework should be turned in physically before the start of the class
    • Emergency: send it to me electronically in standard formats.