Adaptive combinatorial design to explore large experimental spaces: approach and validation.

L. V. Lejay, Dennis Shasha, P. M. Palenchar, A. Y. Kouranov, A. A. Cruikshank, M. F. Chou, Gloria Coruzzi

Research output: Contribution to journalArticle

Abstract

Systems biology requires mathematical tools not only to analyse large genomic datasets, but also to explore large experimental spaces in a systematic yet economical way. We demonstrate that two-factor combinatorial design (CD), shown to be useful in software testing, can be used to design a small set of experiments that would allow biologists to explore larger experimental spaces. Further, the results of an initial set of experiments can be used to seed further 'Adaptive' CD experimental designs. As a proof of principle, we demonstrate the usefulness of this Adaptive CD approach by analysing data from the effects of six binary inputs on the regulation of genes in the N-assimilation pathway of Arabidopsis. This CD approach identified the more important regulatory signals previously discovered by traditional experiments using far fewer experiments, and also identified examples of input interactions previously unknown. Tests using simulated data show that Adaptive CD suffers from fewer false positives than traditional experimental designs in determining decisive inputs, and succeeds far more often than traditional or random experimental designs in determining when genes are regulated by input interactions. We conclude that Adaptive CD offers an economical framework for discovering dominant inputs and interactions that affect different aspects of genomic outputs and organismal responses.

Original languageEnglish (US)
Pages (from-to)206-212
Number of pages7
JournalSystems biology
Volume1
Issue number2
DOIs
StatePublished - Dec 2004

Fingerprint

Combinatorial Design
Approach Space
Adaptive Design
Research Design
Experimental design
Design of experiments
Systems Biology
Arabidopsis
Genes
Experiment
Genomics
Seeds
Software
Interaction
Gene
Experiments
Software Testing
Software testing
False Positive
Demonstrate

ASJC Scopus subject areas

  • Biotechnology
  • Cell Biology
  • Genetics
  • Molecular Biology
  • Molecular Medicine
  • Modeling and Simulation

Cite this

Adaptive combinatorial design to explore large experimental spaces : approach and validation. / Lejay, L. V.; Shasha, Dennis; Palenchar, P. M.; Kouranov, A. Y.; Cruikshank, A. A.; Chou, M. F.; Coruzzi, Gloria.

In: Systems biology, Vol. 1, No. 2, 12.2004, p. 206-212.

Research output: Contribution to journalArticle

Lejay, L. V. ; Shasha, Dennis ; Palenchar, P. M. ; Kouranov, A. Y. ; Cruikshank, A. A. ; Chou, M. F. ; Coruzzi, Gloria. / Adaptive combinatorial design to explore large experimental spaces : approach and validation. In: Systems biology. 2004 ; Vol. 1, No. 2. pp. 206-212.
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