An integer optimization algorithm for robust identification of non-linear gene regulatory networks

BMC Systems Biology

Volumn 6, Issue , 2012, Pages

  Chemmangattuvalappil, Nishanth ^a   Task, Keith ^a   Banerjee, Ipsita ^a  

^a UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Bootstrapping; Gene regulatory networks; Integer programming; Non linear dynamics; Optimization algorithm; Robust network identification; S system

Indexed keywords

ESCHERICHIA COLI;

TRANSCRIPTOME;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BIOLOGY; DNA REPAIR; ESCHERICHIA COLI; GENE REGULATORY NETWORK; GENETICS; METHODOLOGY; NONLINEAR SYSTEM; UNCERTAINTY;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DNA REPAIR; ESCHERICHIA COLI; GENE REGULATORY NETWORKS; MODELS, GENETIC; NONLINEAR DYNAMICS; TRANSCRIPTOME; UNCERTAINTY;

EID: 84865534080     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-6-119     Document Type: Article

References (33)

1. Kabir M, Noman N, Iba H. Reverse engineering gene regulatory network from microarray data using linear time-variant model. BMC Bioinform 2010, 11(Suppl 1):S56.
2. Bansal M, Belcastro V, Ambesi-Impiombato A, di Bernardo D. How to infer gene networks from expression profiles. Mol Syst Biol 2007, 3:122.
3. Huang S. Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery. J Mole Med 1999, 77(6):469-480.
4. Shmulevich I, Dougherty ER, Kim S, Zhang W. Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinform 2002, 18(2):261-274.
5. Chen X-W, Anantha G, Wang X. An effective structure learning method for constructing gene networks. Bioinform 2006, 22(11):1367-1374.
6. Imoto S, Goto T, Miyano S. Estimation of genetic networks and functional structures between genes by using Bayesian network and nonparametric regression. Pac symp Biocomput 2002, 7:12.
7. Zhou X, Wang X, Pal R, Ivanov I, Bittner M, Dougherty ER. A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinform 2004, 20(17):2918-2927.
8. Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat Genet 2005, 37(4):382-390. 10.1038/ng1532, 15778709.
9. Soranzo N, Bianconi G, Altafini C. Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: synthetic versus real data. Bioinform 2007, 23(13):1640-1647.
10. Yu J, Smith VA, Wang PP, Hartemink AJ, Jarvis ED. Advances to Bayesian network inference for generating causal networks from observational biological data. Bioinform 2004, 20(18):3594-3603.
11. Zou M, Conzen SD. A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data. Bioinform 2005, 21(1):71-79.
12. Kimura S, Nakayama S, Hatakeyama M. Genetic network inference as a series of discrimination tasks. Bioinform 2009, 25(7):918-925.
13. Yeung MKS, Tegnér J, Collins JJ. Reverse engineering gene networks using singular value decomposition and robust regression. Proc Natl Acad Sci 2002, 99(9):6163-6168. 10.1073/pnas.092576199, 122920, 11983907.
14. Bansal M, Gatta GD, di Bernardo D. Inference of gene regulatory networks and compound mode of action from time course gene expression profiles. Bioinform 2006, 22(7):815-822.
15. Liu P-K, Wang F-S. Inference of biochemical network models in S-system using multiobjective optimization approach. Bioinform 2008, 24(8):1085-1092.
16. Kikuchi S, Tominaga D, Arita M, Takahashi K, Tomita M. Dynamic modeling of genetic networks using genetic algorithm and S-system. Bioinform 2003, 19(5):643-650.
17. Kimura S, Ide K, Kashihara A, Kano M, Hatakeyama M, Masui R, Nakagawa N, Yokoyama S, Kuramitsu S, Konagaya A. Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm. Bioinform 2005, 21(7):1154-1163.
18. Thomas R, Mehrotra S, Papoutsakis ET, Hatzimanikatis V. A model-based optimization framework for the inference on gene regulatory networks from DNA array data. Bioinform 2004, 20(17):3221-3235.
19. Vilela M, Chou I-C, Vinga S, Vasconcelos A, Voit E, Almeida J. Parameter optimization in S-system models. BMC Syst Biol 2008, 2(1):35. 10.1186/1752-0509-2-35, 2333970, 18416837.
20. Morishita R, Imade H, Ono I, Ono N, Okamoto M. Finding multiple solutions based on an evolutionary algorithm for inference of genetic networks by S-system. Evolutionary Computation, 2003 CEC '03 The 2003 Congress on: 8-12 Dec. 2003 2003 2003, 615-622. Vol. 611.
21. Thattai M, van Oudenaarden A. Intrinsic noise in gene regulatory networks. Proc Natl Acad Sci 2001, 98(15):8614-8619. 10.1073/pnas.151588598, 37484, 11438714.
22. Vinje WE, Gallant JL. Sparse Coding and Decorrelation in Primary Visual Cortex During Natural Vision. Sci 2000, 287(5456):1273-1276.
23. DeWeese MR, Wehr M, Zador AM. Binary Spiking in Auditory Cortex. J Neurosci 2003, 23(21):10.
24. Leclerc RD. Survival of the sparsest: robust gene networks are parsimonious. Mol Syst Biol 2008, 4:213. 2538912, 18682703.
25. Banerjee I, Maiti S, Parashurama N, Yarmush M. An integer programming formulation to identify the sparse network architecture governing differentiation of embryonic stem cells. Bioinform 2010, 26(10):1332-1339.
26. Efron B, Tibshirani RJ. An introduction to bootstrap 1993, Chapman and Hall, New York.
27. Sutton MD, Smith BT, Godoy VG, Walker GC. THE SOS RESPONSE: Recent Insights into umuDC-Dependent Mutagenesis and DNA Damage Tolerance. Annu Rev Genet 2000, 34(1):479-497. 10.1146/annurev.genet.34.1.479, 11092836.
28. Ronen M, Rosenberg R, Shraiman BI, Alon U. Assigning numbers to the arrows: Parameterizing a gene regulation network by using accurate expression kinetics. Proc Natl Acad Sci 2002, 99(16):10555-10560. 10.1073/pnas.152046799, 124972, 12145321.
29. Index of /mcb/UriAlon/Papers/SOSData [http://www.weizmann.ac.il/mcb/UriAlon/Papers/SOSData/].
30. Papadimitriou CH, Steiglitz K. Combinatorial optimization: Algorithms and complexity 1998, Dover, Mineola, NY.
31. Yao X. Evolutionary computation: Theory and applications 1999, World Scientific Publishing, Singapore.
32. Gutenkunst RN, Waterfall JJ, Casey FP, Brown KS, Myers CR, Sethna JP. Universally Sloppy Parameter Sensitivities in Systems Biology Models. PLoS Comput Biol 2007, 3(10):e189.
33. Wehrens R, Putter H, Buydens LMC. The bootstrap: a tutorial. Chemometrics and Intelligent Laboratory Syst 2000, 54:18.