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Biosystems project

What This Is

This program is a cross-platform command-line interface for interacting with the Kyoto Encyclopedia of Genes and Genomes (KEGG). It provides easy commands to find, list, and get information on any compound, enzyme, or reaction in the KEGG database. It also provides a depth-first search algorithm for finding a series biological pathways that convert a given starting compound to a desired end compound. This can be done either through a pathway (KEGG module) based search or a reaction based search, in search-pathway and search-reactions commands, respectively.

See KEGG here (Kyoto Encyclopedia of Genes and Genomes)

This project was in partial completement of BEE3600 - Molecular and Cellular Bioenginerring, Cornell University

Dependencies

  • python >3.0
  • urllib3; for information see Repository here
  • certifi; to install: pip install certify
  • requests; to install: pip install requests

How to use

	This is a command-line interface program for interacting with
	the KEGG database. It operates by entering lines in the following
	format:
		<command> <arguement 1> <arguement 2> ... <arguement n> <ENTER>

	where < > is replaced by the meaning of the text within (WITHOUT the brackets
	themselves), [ ] contains optional values, and * is any possible existing term. 
	The number of arguements required for each command various. Here is a list of 
	all commands, the arguements required (if any), and what they do:

		help (no arguements) - print this message
		exit (no arguements) - end program
		list <database> - lists all entries in the database specified (see below for possible databases)
		find <database> <term to search> - returns all entries in database with term specified
		get <kegg id> - returns information about object with specified kegg id
		info <database> - returns information about the database
		gibbs <reaction id> - returns Gibbs Free Energy [kcal/mol] of reaction using alternative databases or 0 on failure
		set <setting> <value> - change settings, see below
		define <database> <name> - will make <name> interchangeable with its kegg id in the cli
		see-defined (no arguements) - see a list of all defined names/kegg ids
		see-settings (no arguements) - print settings
		search-pathway[s] <compound A> <compound B> [depth-limit] - depth-first search of biological pathway from A to B
		search-reaction[s] <compound A> <compound B> [depth-limit] - depth-first search of reaction series from A to B
		save-solution <filename> - after either search-* command, will save the solution in a txt file
		save-full-solution <filename> - like save-solution, but saves ALL KEGG data of the solution
	
	save-* commands do not need to be called immediately after search-* commands, but will always refer to the latest
	search-* command results. 
	
	The databases in KEGG include but are not limited to:
		reaction[s]
		enzyme[s]
		compound[s]
		pathway[s]

	Possible settings to change are:
		list-limit -> maximum number of elements to output from a list, set to -1 for no limit
		output-line-limit -> maximum number of lines to output (excluding lists), set to -1 for no limit
		depth-limit -> Equals x such that O(n^x) is effectively the runtime; the 
			bigger this number is, the exponentially larger the loading time. Too high of a number may 
			improve search results but will exponentially increase search time. Using a specific depth-limit
			in the search-* commands overrides this setting for that run (only).
		verbose -> prints detailed output on what the program is doing, either True/False
		solve-gibbs -> if true will solve attempt to find Gibbs Free Energy
	
	set <setting> <value> command changes the setting, verbose and solve-gibbs can only be true or false.
	
	See https://kegg.jp for more information on KEGG.

License

This project is under the MIT License. See LICENSE.txt for more details.

Possible Future Improvements

It is unknown if this project will remain under active developement/support in the future, but there some improvements which may be made to this program:

  • breadth-first search algorithm
  • thread optimization to reduce runtime
    • (A thread class based on Python threading.Thread was made, but not implemented)
  • parsing additional databases for pH, temperature, and other reaction conditions

And as always, no program is made perfect; feel free to report issues or fork.

(Code) Contributors

  • Shaumik Ashraf
  • Aaron-Earle Richardson

A special thanks to Professor Buzz Barstow of Cornell University for mentoring and encouraging this project.