{ "metadata": { "name": "", "signature": "sha256:e05e3dfc60d83e593fee372dc9629cd81d5978c004d6a6662e5e30c865ad41ca" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This example is taken from the YAHMM wiki on silent states and edited." ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Global Sequence Alignment using YAHMM" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Global sequence alignment is a problem in bioinformatics which involves aligning two sequences against each other in the maximally likely way. Lets say that you have the two sequences, ACT and ACG, and you wish to align them. The most obvious alignment is:\n", "\n", "```\n", "ACT\n", "||\n", "ACG\n", "```\n", "It's a close match, but one sequence has a G and one has a T at the end. You know from biology that nucleotides can mutate over time, be removed, or be added. In this case, you have to weigh the two hypotheses of 'did this nucleotide mutate' vs 'was a nucleotide removed and then another one added later'. Almost always the nucleotide mutation hypothesis wins out.\n", "\n", "![](http://www.cs.tau.ac.il/~rshamir/algmb/00/scribe00/html/lec06/img106.gif)\n", "