The program gives two network as inputs and returns a global alignment.

Here is a template for running the program:

./NETAL net1 net2 [-a av] [-b bv] [-c cv] [-i iv]

Here is an example of running the program:

./NETAL yeast human -a 0.0001 -b 0.6 -c 0.5 -i 2

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net1: Name of the first network
net2: Name of the second network

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-a av:  an option for defining value of parameter a
av is a float number between 0 and 1.It is a value for parameter a which controls the weight of similarity and interaction scores. If av=1 then the program considers only similarity score and if av=0 then it considers only interaction score. The preferred value for av is 0.0001.

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-b bv: an option for defining value of parameter b
bv is a float number between 0 and 1.It is a value for parameter a which controls the weight of biological and topological similarities. If bv=1 then the program considers only biological similarity and if bv=0 then it considers only topological similarity. If you don't want to use any biological data you should set bv=0 and you don't need to provide any file for biological similarities. Default value for bv is 0.

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-c cv: an option for defining value of parameter c
cv is a float number between 0 and 1.It is a value for parameter a which controls the weight of main nodes and their neighbors similarities. If cv=0 then the program considers only similarity of main nodes and if cv=1 then it considers only similarities of neighbors of main nodes. If you don't want to use any biological data it is preferred to set cv=1. Default value for bv is 1.

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-i iv: an option for defining value of parameter i
iv is a non-negative integer number .It defines the number of iterations for computing similarities. The preferred value for i is 2.

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Input files :


You should provide files "net1.tab" and "net2.tab" with following rules:

1- Files should be tab-separated.
2- Each line contains an interaction.
3- Each line starts with a string as the name of a protein in the interaction followed by a tab  and a string as the name of another protein in the interaction.

Here is a sample for "net1.tab" :

aa	ab
bb	acd
a1	a3d
bd	re5

If you want to use biological similarity data for proteins, you should provide files "net1-net1.val","net2-net2.val" and "net1-net2.val" with following rules:

1- Files should be tab-separated.
2- In "net1-net2.val" Each line starts with two strings and ends with a value. The first string is a name of a protein in net1. The second string which is separated by a tab is a name of a protein in net2. The value at the end of the line which is separated from second string by a tab is a float number that is a measurement for similarity between the first protein and the second one.
3- In "net1-net1.val" and "net2-net2.val" each line starts with a string as the name of a protein. In the second column you need to repeat the name. In the third column there is float number which is used to scale similarity of other proteins this one.

Here is a sample for "net1-net2.val"

aa	cc	65.0
bb	dd	32.4
ab	cd	23.6


Here is a sample for "net1-net1.val"

aa	aa	128.0
bb	bb	94.7
ab	ab	30.5

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Output files :


The program outputs two files "net1-net2.algn" and "net1-net2.eval". The first one contains global alignment of two networks, each matched pair in a line, and the later contains some statistics about the alignment.

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