Lecture GK-1

Introduction; Pairwise sequence alignment

Aims

• To place bioinformatics in a wider context.
• To introduce the basic principles of pairwise sequence alignment.

Objectives

After this lecture you will be able to:

• discuss a range of experimental methods, the kinds of data that these generate, and examples of biological questions that these can help to address;
• describe and compute of simple measures of sequence similarity;
• describe the relationship between dotplots and sequence alignments;
• implement and apply a dynamic programming algorithm to find an optimal pairwise sequence alignment;
• describe the difference between global and local alignment algorithms.

Supplementary Material

The lecture handout, featuring some of the lecture slides, is available on-line (one per page, four per page).

Web-based programs illustrating topics from the lecture:

• Dotplot
• Global Alignment
• Local Alignment

Programs described in the lecture (local access only):

• dotplot.c
• Dotplot.java
• global_alignment.c
• GlobalAlignment.java

Links to Wikipedia pages describing some experimental methods:

• DNA sequencing
• Protein sequencing
• X-ray crystallography
• Nuclear magnetic resonance (NMR) spectroscopy
• Cryo-electron microscopy
• Small-angle X-ray scattering
• DNA microarray
• RNA-Seq
• Two-dimensional gel electrophoresis
• Mass spectrometry
• In situ hybridization