Creation of Four Different Algorithms for the Transmembrane Segment Identification Problem for Proteins

 

(A Human-Competitive Result Produced by Genetic Programming)

 

The Result

Genetic programming evolved four different algorithms for the transmembrane segment identification problem for proteins as described in Sections 18.8 and 18.10 of Genetic Programming II: Automatic Discovery of Reusable Programs (Koza 1994) and sections 16.5 and 17.2 of Genetic Programming III: Darwinian Invention and Problem Solving (Koza, Bennett, Andre, and Keane 1999). One of these algorithms is the "0-2-4 rule" described in section 16.5 of Genetic Programming III, as shown in the table below.

Residue

Increment

A, F, I, L, M, or V

0

C, D, G, H, K, N, P, Q, R, S, T, W, or Y

+2

E

+4

Basis for Claim of Human-Competitiveness

The out-of-sample error rates for all four algorithms created by genetic programming  are better than the error rates for the three human-written algorithms (the first three rows of table 16.5 of Genetic Programming III: Darwinian Invention and Problem Solving (Koza, Bennett, Andre, and Keane 1999).

Referring to the eight criteria in chapter 1 of Genetic Programming III: Darwinian Invention and Problem Solving (Koza, Bennett, Andre, and Keane 1999) for establishing that an automatically created result is competitive with a human-produced result, the automatic synthesis of algorithms for the transmembrane segment identification problem for proteins satisfies the following two criteria:

(B) The result is equal to or better than a result that was accepted as a new scientific result at the time when it was published in a peer-reviewed journal.

(E) The result is equal to or better than the most recent human-created solution to a long-standing problem for which there has been a succession of increasingly better human-created solutions. 

References

Koza, John R. 1994a. Genetic Programming II: Automatic Discovery of Reusable Programs. Cambridge, MA: The MIT Press.

Koza, John R., Bennett III, Forrest H, Andre, David, and Keane, Martin A. 1999a. Genetic Programming III: Darwinian Invention and Problem Solving. San Francisco, CA: Morgan Kaufmann.


· The home page of Genetic Programming Inc. at www.genetic-programming.com.

· For information about the field of genetic programming and the field of genetic and evolutionary computation, visit www.genetic-programming.org

· The home page of John R. Koza at Genetic Programming Inc. (including online versions of most published papers) and the home page of John R. Koza at Stanford University

· For information about John Koza’s course on genetic algorithms and genetic programming at Stanford University

· Information about the 1992 book Genetic Programming: On the Programming of Computers by Means of Natural Selection, the 1994 book Genetic Programming II: Automatic Discovery of Reusable Programs, the 1999 book Genetic Programming III: Darwinian Invention and Problem Solving, and the 2003 book Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Click here to read chapter 1 of Genetic Programming IV book in PDF format.

· 3,440 published papers on genetic programming (as of November 28, 2003) in a searchable bibliography (with many on-line versions of papers) by over 880 authors maintained by William Langdon’s and Steven M. Gustafson.

· For information on the Genetic Programming and Evolvable Machines journal published by Kluwer Academic Publishers

· For information on the Genetic Programming book series from Kluwer Academic Publishers, see the Call For Book Proposals

· For information about the annual Genetic and Evolutionary Computation (GECCO) conference (which includes the annual GP conference) to be held on June 26–30, 2004 (Saturday – Wednesday) in Seattle and its sponsoring organization, the International Society for Genetic and Evolutionary Computation (ISGEC). For information about the annual Euro-Genetic-Programming Conference to be held on April 5-7, 2004 (Monday – Wednesday) at the University of Coimbra in Coimbra Portugal. For information about the 2003 and 2004 Genetic Programming Theory and Practice (GPTP) workshops held at the University of Michigan in Ann Arbor. For information about Asia-Pacific Workshop on Genetic Programming (ASPGP03) held in Canberra, Australia on December 8, 2003. For information about the annual NASA/DoD Conference on Evolvable Hardware Conference (EH) to be held on June 24-26 (Thursday-Saturday), 2004 in Seattle.


Last updated on December 28, 2003