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7. Hidden Markov Models (Parte 2) (pdf, it, 413 KB, 4/28/10)

7. Hidden Markov Models (Parte 2) (pdf, it, 413 KB, 4/28/10)

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Allineamento multiplo di sequenze<br />

• Utilizzando questa arch<strong>it</strong>ettura ed l’algor<strong>it</strong>mo di<br />

V<strong>it</strong>erbi si possono allineare sequenze<br />

• Prendiamo la pronuncia di bioinformatica in<br />

nordirlandese “by-in-fer-maah-dics” e vediamo<br />

due percorsi diversi sull’arch<strong>it</strong>ettura appena<br />

creata<br />

V<strong>it</strong>torio Murino Riconoscimento e Classificazione per la Bioinformatica 1<strong>10</strong><br />

1<strong>10</strong><br />

START<br />

.1<br />

D<br />

V<strong>it</strong>erbi path 1<br />

1<br />

Probabil<strong>it</strong>à 1 di avere una<br />

cancellazione!<br />

for=0.6 ma=0.5<br />

by=.8<br />

in=0.7<br />

tics=0.6<br />

1 .8<br />

oh=0.95<br />

1 .9 .9 1 .9<br />

fah=0.2 mah=0.3<br />

bah=.1 iyn=0.2<br />

ah=0.05 fer=0.1 fer=0.1<br />

may=0.19<br />

dics=0.2 dics=0.2<br />

bar=.1 un=0.1<br />

tikz=0.2<br />

fur=0.1 maah=.01 maah=.01<br />

• Path 1<br />

P = (1*.8)*(.1*1)*(1*0.7)*(0.9*0.1)*(0.9*0.01)*<br />

(1*0.2)*(0.9) = 8.2 x <strong>10</strong>-6<br />

V<strong>it</strong>torio Murino Riconoscimento e Classificazione per la Bioinformatica 111<br />

111<br />

END<br />

32

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