Lecture_7_part2_phylogenetics

# This method works best when it is used to test or

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Unformatted text preview: si( le/ child ) + δi, t} + minj {sj( right child ) + δj, t} Sankoﬀ Algorithm (cont.) Sankoﬀ Algorithm (cont.) st(v) = mini {si(u) + δi, t} + minj{sj(w) + δj, t} st(v) = mini {si(u) + δi, t} + minj{sj(w) + δj, t} si ( u δi, A ) su m A 0 0 0 T ∞ 3 ∞ G ∞ 4 C min sA(v) = 0 i{si(u) + δi, A} + minj{sj(w) + δj, A} ∞ 9 Sankoﬀ Algorithm (cont.) st(v) = mini {si(u) + δi, t} + minj{sj(w) + δj, t} sj ( u δj, A ) su m A ∞ 0 ∞ T ∞ 3 ∞ ∞ G ∞ 4 ∞ ∞ C 0 9 9 sA(v) = mini{si(u) + δi, A} 0 minj{ + 9 = 9 sj(w) + δj, A} Sankoﬀ Algorithm (cont.) Repeat for right subtree Repeat for T, G, and C 5 9/24/13 Sankoﬀ Algorithm (cont.) Repeat for root Sankoﬀ Algorithm (cont.) Smallest score at root is minimum weighted In this case, 9 – parsimony score so label with T Sankoﬀ Algorithm: Traveling down the Tree •  The scores at the root vertex have been computed by going up the tree •  Aner the scores at root vertex are computed the Sankoﬀ algorithm moves down the...
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## This note was uploaded on 02/10/2014 for the course CS 425 taught by Professor Asaben-hur during the Fall '13 term at Colorado State.

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