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IBM Systems Journal
Information-Based Medicine   Volume 46, Number 1, 2007
Table of contents: HTMLPDF This article: HTMLPDF   Copyright info

A graph-theoretical approach for pattern discovery in epidemiological research - References

 by R. A. Mushlin,
A. Kershenbaum,
S. T. Gallagher,
and T. R. Rebbeck
Cited references

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  15. D. V. Conti, V. Cortessis, J. Molitor, and D. C. Thomas, “Bayesian Modeling of Complex Metabolic Pathways,” Human Heredity 56, Nos. 1–3, 83–93 (2003).
  16. V. Cortessis and D. C. Thomas, “Toxicokinetic Genetics: An Approach to Gene-Environment and Gene-Gene Interactions in Complex Metabolic Pathways,” International Agency for Research on Cancer Scientific Publication 157, 127–150 (2004).
  17. J. Millstein, D. Conti, F. Gilliland, and W. Gauderman, “A Testing Framework for Identifying Susceptibility Genes in the Presence of Epistasis,” American Journal of Human Genetics 78, No. 1, 15–27 (2006).
  18. G. Alexe, S. Alexe, Y. Crama, S. Foldes, P. Hammer, and B. Simeone, “Consensus Algorithms for the Generation of All Maximal Bicliques,” Discrete Applied Mathematics 145, No. 1, 11–21 (2004).
  19. M. D. Ritchie, L. W. Hahn, N. Roodi, R. Bailey, W. D. Dupont, F. F. Parl, and J. H. Moore, “Multifactor Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer,” American Journal of Human Genetics 69, No. 1, 138–147 (2001).
  20. L. Bastone, M. Reilly, D. L. Rader, and A. S. Foulkes, “MDR and PRP: A Comparison of Methods for High-Order Genotype-Phenotype Associations,” Human Heredity 58, No. 2, 82–92 (2004).
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