The theory behind Sequence alignment and sequence homology. We discuss sequence substitutions, optimal alignment strategies, BLOSUM, BLAST, and ClustalW.

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Chapters:
00:00 Welcome back
00:10 Pairwise alignment of sequences
01:25 Global versus Local pairwise alignment
03:50 Alignments require a scoring function
04:45 Simplistic scoring function - Additive scoring with a linear gap penalty
06:28 Improving the scoring function - The affine gap penalty
09:51 DNA and Protein level alignment can vary a lot
13:08 DNA substitution probabilities, Transition versus Transversion
15:34 Amino acid substitution probabilities
17:16 The Point accepted mutation (PAM) matrix
19:05 The BLOcks SUbstitution Matrix (BLOSUM)
23:27 A fun fact about the default BLOSUM62 matrix
24:19 Differences between PAM and BLOSUM
25:52 The optimal alignment - The Smith-Waterman algorithm
28:00 Dot Plots - visualizing pairwise sequence alignments
31:19 The Basic Local Alignment Search Tool (BLAST) algorithm
33:49 Overview of different BLAST algorithms
35:23 Evaluating BLAST alignments (E-values)
36:53 Rule of thumb for sequence homology
38:13 Multiple Sequence Alignment (MSA)
41:06 Parameters affecting Multiple Sequence Alignment (MSA)
41:52 Smith-Waterman on an N-dimensional dot plot and runtime
44:04 ClustalW and real-time Multiple Sequence Alignment (MSA)
45:48 Interpreting Multiple Sequence Alignment (MSA) results

This is a live-stream recording of the MSc and PhD lecture series: #Bioinformatics for plant and animal sciences, given digitally during the Covid19 pandemic at the Humboldt University in Berlin organized and lectured by Dr Danny Arends.

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