@conference { koza:1998:cpeupm,
	title = {Classifying Proteins as Extracellular using Programmatic Motifs and Genetic Programming},
	year = {1998},
	month = {"5-9 " # may},
	pages = {212--217},
	publisher = {IEEE Press},
	type = {inproceedings},
	address = {Anchorage, Alaska, USA},
	abstract = {As newly sequenced proteins are deposited into the
                 world' s ever-growing archive of protein sequences,
                 they are typically immediately tested by various
                 computerized algorithms for clues as to their
                 biological structure and function. One question about a
                 new protein involves its cellular location - that is,
                 where the protein resides in a living organism
                 (extracellular, intracellular, etc.). A 1997 paper
                 reported a human-created five-way algorithm for
                 cellular location created using statistical techniques
                 with 76% accuracy.

                 This paper describes a two-way classification algorithm
                 that was evolved using genetic programming with 83%
                 accuracy for determining whether a protein is
                 extracellular. Unlike the statistical calculation, the
                 genetically evolved algorithm employs a large and
                 varied arsenal of computational capabilities, including
                 arithmetic functions, conditional operations,
                 subroutines, iterations, memory, data structures,
                 set-creating operations, macro definitions, recursion,
                 etc. The genetically evolved classification algorithm
                 can be viewed as an extension (which we call a
                 programmatic motif) of the conventional notion of a
                 protein motif. The genetically evolved program
                 constitutes an instance of an evolutionary computation
                 technique producing a solution to a problem that is
                 competitive with that produced using human
                 intelligence.},
	keywords = {genetic algorithms, genetic programming},
	URL = {http://www.genetic-programming.com/jkpdf/icec1998.pdf},
	author = { Koza, John R.  and  III, Forrest H Bennett  and  Andre, David}
}