# Alignment Algorithm Demo

Scroll down for the applet

This applet gives a demonstration of several different alignment algorithms. Some algorithms determine an optimal alignment, some only the edit cost. The values in each cell are only displayed if there is room.

The green cells indicate a cell which has been computed by the algorithm. A blue cell indicates that this cell is currently being computed.

Note that some of these algorithms, such as Ukkonen's Algorithm, do not actually compute using this 2d matrix. In these cases, the animated matrix shows cells that are implicitly calculated by the algorithm.

#### Standard DPA

This is the simple DPA for point mutation costs, match=0, mismatch=1, insert/delete=1. Each cell of the matrix, D[i][j], contains the edit cost for the sequences s1[1..i] and s2[1..j]. An optimal alignment is drawn through the matrix

#### Lazy DPA

This is a modified version of the standard DPA which computes a smaller region of the D matrix (runs in O(nd) time).

#### Ukkonen's Algorithm

Ukkonen's algorithm runs in O(d*d + n) time. This algorithm does not use the D matrix like the other DPA algorithms. However, Ukkonen's algorithm is shown here operating of the standard matrix to give an idea as to which cells of the DPA matrix it computes. Blue cells indicate a cell currently being computed. Green cells indicate cells that have already been computed.

#### Hirschberg

Hirschberg presented a modification of the DPA that allows an optimal alignment to be found in O(n) space. Green cells are cells that have been computed and are currently stored. Yellow cells indicate cells that are known to lie on the optimal alignment.

#### Linear DPA

This algorithm is the O(n2) DPA for linear gap costs, with gaps costed as a+b*k where a=3, b=1, matches=0, mismatches=0.

#### Ukkonen Linear

This is Ukkonen's algorithm for linear gap costs (same costs as for the Linear DPA case).

You need java installed to view this demo.