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InfoEvolve™
Author(s) -
VAIDYANATHAN GANESH
Publication year - 2004
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1310.019
Subject(s) - computer science , identification (biology) , suite , variance (accounting) , set (abstract data type) , key (lock) , data mining , homogeneous , mathematics , botany , computer security , accounting , archaeology , biology , business , history , programming language , combinatorics
A bstract : InfoEvolve™ is a unified suite of data mining and empirical modeling tools capable of discovering low‐bias and low‐variance solutions to complex processes. The method is based on a common set of principles involving information theory and genetic algorithms. InfoEvolve™ can also discover multiple strategies embedded in complex data sets for achieving a desired target or goal. This latter aspect may prove to be very useful in drug design. The paper analyzes the following: InfoEvolve™ from a theoretical standpoint; a conceptual overview of InfoEvolve™ with a short description of the modeling method; the method using the example of homogeneous identification of DNA from an analysis of its melting curve behavior; and key learnings and additional applications of the technology for both drug design and genome analysis.