Create a tool which will allow biologists to more eaisly study biochemical pathways.

An algorithm was developed by Ferhat, Tamer, et al., which produces the alignment of two pathways.
The idea is that by giving the user many options for input and output, this algorithm becomes much more biologically useful. 

The trivial:
1. Create a user-interface that allows the user to select from a database (eg. KEGG) an organism-pathway pair, and 
   another organism-pathway pair, as for input into the algorithm.
2. Allow users to input their own pathways.
3. After algnments are given, allow the user to view the details by mousing-over entites. Details include:
a. Alignment score of the aligned entity. 
b. Label terms for the entity

The non-trivial
Devise schemes for representing the output of the alignments that are easy to understand visually by
   
1. Presenting two graphs next to eachother:
   
a. And color-coordinate entities that are aligned.
b. With lines drawn between aligned entities (or that appear on mouse-over).
c. Large numbers printed on the face of nodes, where each number appears on both of the aligned entities.
d. Use a combination of color-coordination and texture to create many distinct looking nodes, such that it is visually easy to
   view the alignment.
e. Allow user to zoom in and out, for viewing of large pathways. Also, allow users to select a subgraph (#1) of nodes when they
   are zoomed in, make a click, and view the graphs of the selected subgraph (#1), along with the subgraph (#2) that represents
   the the entities that are aligned to subgraph #1.
f. Simply output the raw data of the alignment that is produced by the program in a text file.
g. Do all of the above

2. Create a single graph from the two, where each node represents an aligned entity-entity pair,and each edge an 
   aligned reaction pair.
   a. All applicable functionalies described above.

References:

	Ferhat Ay, Tamer Kahveci, Valerie de Crecy-Lagard,
	Consistent alignment of metabolic pathways without any abstraction in modeling,
	International Conference on Computational Systems Biology (CSB), 2008.
	
	Mehmet Koyutürk, Yohan Kim, Umut Topkara, Shankar Subramaniam, Wojciech Szpankowski, Ananth Grama. Journal of 
  	Computational Biology. March 1, 2006, 13(2): 182-199. doi:10.1089/cmb.2006.13.182. 

	

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