配列情報解析の3人の専門家、浅井潔、加藤和貴、Martin Frith、が講義する。
Course content:
Critical thinking versus cargo cult science, and dangers of jargon.
Diversity of genetic sequence data.
Examples of knowledge we can gain by comparing sequences.
How genetic sequences mutate and evolve.
Evolutionary relationships: homology, orthology, and paralogy.
Repeats: transposable elements and tandem repeats. Facts versus definitions.
Finding clumps in sequential data, by dynamic programming. Facts versus definitions. Finding one optimal clump: Kadane's algorithm for one sequence, Smith-Waterman algorithm for comparing two sequences. Problems and solutions when there is more than one clump.
Probability models: all models are wrong, but some are useful. Hidden Markov models.
Similar sequences occurring by chance, p-values and E-values, multiple testing.
Multiple sequence alignment: aligning more than two sequences to each other.
Fast algorithms: seed-and-extend alignment versus alignment-free sequence comparison. Spaced seeds and subset seeds. Suffix arrays. Sampling a subset of positions in a sequence.