ATPG for Cancer Therapy



Cancer and other gene related diseases are usually caused by a failure in the signaling pathway between genes and cells. These failures can occur in different areas of the gene regulatory network, but can be abstracted as faults in the regulatory function. For effective cancer treatment, it is imperative to identify faults and select appropriate drugs to treat the faults.


Gene Regulatory Network Boolean Network Conjunctive Normal Form Sequential Circuit Fault Rectification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Lin, P. K., Khatri, S.P.: Efficient cancer therapy using Boolean networks and Max-SAT-based ATPG. Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on. IEEE, 87–90 (2011)Google Scholar
  2. 2.
    Lin, P. K., Khatri, S.: Application of Max-SAT-based ATPG to optimal cancer therapy design. BMC Genomics 13(6) S–5 (2012)Google Scholar
  3. 3.
    Guelzim N. et al.: Topological and causal structure of the yeast transcriptional regulatory network, Nat. Genet. (31), 60–63 (2002)CrossRefGoogle Scholar
  4. 4.
    Kauffman, S.A.: Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol. 22(3), 437–467 (1969)CrossRefGoogle Scholar
  5. 5.
    Layek R., Datta, A., Bittner, M., Dougherty, E.R.: Cancer therapy design based on pathway logic. Bioinformatics. 27(4), 548–555 (2011)CrossRefGoogle Scholar
  6. 6.
    Jacob, F., Monod, J., Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3(3), 318–356 (1961)CrossRefGoogle Scholar
  7. 7.
    Larrabee, T., Efficient Generation of Test Patterns Using Boolean Difference. Proc. of the Intl. Test Conf. 795–801 (1989)Google Scholar
  8. 8.
    Stephan, P., Brayton, R.K., Sangiovanni-Vincentelli, A.L.: Combinational test generation using satisfiability, Comput.-Aided Des. Integr. Circuits Syst. IEEE Trans. 15(9) 1167–1176, Sept. (1996)CrossRefGoogle Scholar
  9. 9.
    Saluja, N.S., Gulati, K., Khatri, S.P.: SAT-based ATPG using multilevel compatible don’t-cares. ACM Trans. Des. Autom. Electron. Syst. 13, 24:1–24:18, April (2008)CrossRefGoogle Scholar
  10. 10.
    Lin, P. K., Khatri, S.P. “Inference of gene predictor set using Boolean satisfiability,” in Genomic Signal Processing and Statistics (GENSIPS), 2010 IEEE International Workshop on, Nov. 2010, pp. 1–4.Google Scholar
  11. 11.
    Corbin, F., Bordeaux, L., Hamadi, Y., Fanchon, E., Trilling, L.: A SAT-based approach to decipher gene regulatory networks. Integrative Post-Genomics, RIAMS, Lyon, (2007)Google Scholar
  12. 12.
    Dubrova, E., Teslenko, M., A SAT-based algorithm for finding attractors in synchronous Boolean networks. IEEE/ACM Trans. Comput. Biol. Bioinforma. 8(5) 1393–1399, Sept. (2011)CrossRefGoogle Scholar
  13. 13.
    Akutsu, T., Hayashida, M., Ching, W.K., Ng, M.K.: Control of Boolean networks: Hardness results and algorithms for tree structured networks. J. Theor. Biol., 244(4) 670–679, (2007)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Langmead, C.J., Jha, S.K.: Symbolic approaches for finding control strategies in Boolean networks. J. Bioinforma. Comput. Biol. 323–338 April (2009)Google Scholar
  15. 15.
    Li, C.M., Manya, F., Planes, J.: Maxsatz,, Accessed 10 July 2011.
  16. 16.
    Li, C., Manya, F., Mohamedou, N., Planes, J.: Exploiting cycle structures in Max-SAT, in Theory and Applications of Satisfiability Testing - SAT 2009, Oliver Kullmann, Ed., vol. 5584 of Lecture Notes in Computer Science, pp. 467–480. Springer, Berlin (2009)Google Scholar
  17. 17.
    Santa Cruz Biotechnology Inc, Santa cruz biotechnology, inc home,, Accessed 15 Aug 2011
  18. 18.
    National Center for Biotechnology Information, Pubmed health - national library of medicine,, Accessed August 15, 2011
  19. 19.
    Faryabi, B., Chamberland, J.-F., G. Vahedi, Datta, A., Dougherty, E.R.: Optimal intervention in asynchronous genetic regulatory networks. IEEE J. Sel. Top. Signal Process. 2(3) 412–423, June (2008)CrossRefGoogle Scholar
  20. 20.
    Abramovici, M., Breuer, M. A., Friedman, A. D.: Digital Systems Testing and Testable Design, Computer Science Press, (1990)Google Scholar
  21. 21.
    Kohavi, Z.: Switching and Finite Automata Theory, Computer Science Series. McGraw-Hill Book Company. (1970)Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Electrical and Computer EngineeringTexas A&M UniversityCollege StationUSA

Personalised recommendations