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InfoEvolve: moving from data to knowledge using information theory and genetic algorithms.

Publication ,  Journal Article
Vaidyanathan, G
Published in: Ann N Y Acad Sci
May 2004

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.

Duke Scholars

Published In

Ann N Y Acad Sci

DOI

ISSN

0077-8923

Publication Date

May 2004

Volume

1020

Start / End Page

227 / 238

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Models, Theoretical
  • Models, Genetic
  • General Science & Technology
  • DNA
  • Computational Biology
  • Algorithms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Vaidyanathan, G. (2004). InfoEvolve: moving from data to knowledge using information theory and genetic algorithms. Ann N Y Acad Sci, 1020, 227–238. https://doi.org/10.1196/annals.1310.019
Vaidyanathan, Ganesh. “InfoEvolve: moving from data to knowledge using information theory and genetic algorithms.Ann N Y Acad Sci 1020 (May 2004): 227–38. https://doi.org/10.1196/annals.1310.019.
Vaidyanathan, Ganesh. “InfoEvolve: moving from data to knowledge using information theory and genetic algorithms.Ann N Y Acad Sci, vol. 1020, May 2004, pp. 227–38. Pubmed, doi:10.1196/annals.1310.019.
Journal cover image

Published In

Ann N Y Acad Sci

DOI

ISSN

0077-8923

Publication Date

May 2004

Volume

1020

Start / End Page

227 / 238

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Models, Theoretical
  • Models, Genetic
  • General Science & Technology
  • DNA
  • Computational Biology
  • Algorithms