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Items: 1 to 20 of 104

1.

A stochastic Markov chain model to describe lung cancer growth and metastasis.

Newton PK, Mason J, Bethel K, Bazhenova LA, Nieva J, Kuhn P.

PLoS One. 2012;7(4):e34637. doi: 10.1371/journal.pone.0034637. Epub 2012 Apr 27.

2.

Entropy, complexity, and Markov diagrams for random walk cancer models.

Newton PK, Mason J, Hurt B, Bethel K, Bazhenova L, Nieva J, Kuhn P.

Sci Rep. 2014 Dec 19;4:7558. doi: 10.1038/srep07558.

3.

Spreaders and sponges define metastasis in lung cancer: a Markov chain Monte Carlo mathematical model.

Newton PK, Mason J, Bethel K, Bazhenova L, Nieva J, Norton L, Kuhn P.

Cancer Res. 2013 May 1;73(9):2760-9. doi: 10.1158/0008-5472.CAN-12-4488. Epub 2013 Feb 27.

4.

A stochastic model for adhesion-mediated cell random motility and haptotaxis.

Dickinson RB, Tranquillo RT.

J Math Biol. 1993;31(6):563-600.

PMID:
8376918
5.

Characterization of endothelial cell locomotion using a Markov chain model.

Lee Y, Markenscoff PA, McIntire LV, Zygourakis K.

Biochem Cell Biol. 1995 Jul-Aug;73(7-8):461-72.

PMID:
8703417
6.

A markov model based analysis of stochastic biochemical systems.

Ghosh P, Ghosh S, Basu K, Das SK.

Comput Syst Bioinformatics Conf. 2007;6:121-32.

7.

Stochastic modelling of a single ion channel: an alternating renewal approach with application to limited time resolution.

Milne RK, Yeo GF, Edeson RO, Madsen BW.

Proc R Soc Lond B Biol Sci. 1988 Apr 22;233(1272):247-92.

PMID:
2454479
8.

A Bayesian method for construction of Markov models to describe dynamics on various time-scales.

Rains EK, Andersen HC.

J Chem Phys. 2010 Oct 14;133(14):144113. doi: 10.1063/1.3496438.

PMID:
20949993
9.

Stochastic model of metastases formation.

Liotta LA, Saidel GM, Kleinerman J.

Biometrics. 1976 Sep;32(3):535-50.

PMID:
963169
10.

Computing short-interval transition matrices of a discrete-time Markov chain from partially observed data.

Charitos T, de Waal PR, van der Gaag LC.

Stat Med. 2008 Mar 15;27(6):905-21.

PMID:
17579926
11.

An orthotopic model of lung cancer to analyze primary and metastatic NSCLC growth in integrin alpha1-null mice.

Chen X, Su Y, Fingleton B, Acuff H, Matrisian LM, Zent R, Pozzi A.

Clin Exp Metastasis. 2005;22(2):185-93.

PMID:
16086239
12.

Genomic analysis of a spontaneous model of breast cancer metastasis to bone reveals a role for the extracellular matrix.

Eckhardt BL, Parker BS, van Laar RK, Restall CM, Natoli AL, Tavaria MD, Stanley KL, Sloan EK, Moseley JM, Anderson RL.

Mol Cancer Res. 2005 Jan;3(1):1-13.

13.

Bias in Markov models of disease.

Faissol DM, Griffin PM, Swann JL.

Math Biosci. 2009 Aug;220(2):143-56. doi: 10.1016/j.mbs.2009.05.005. Epub 2009 Jun 16.

PMID:
19538974
14.

Synchronized dynamics and non-equilibrium steady states in a stochastic yeast cell-cycle network.

Ge H, Qian H, Qian M.

Math Biosci. 2008 Jan;211(1):132-52. Epub 2007 Oct 23.

PMID:
18048065
15.

Derivatives of the stochastic growth rate.

Steinsaltz D, Tuljapurkar S, Horvitz C.

Theor Popul Biol. 2011 Aug;80(1):1-15. doi: 10.1016/j.tpb.2011.03.004. Epub 2011 Apr 2.

16.
17.

Random migration processes between two stochastic epidemic centers.

Sazonov I, Kelbert M, Gravenor MB.

Math Biosci. 2016 Apr;274:45-57. doi: 10.1016/j.mbs.2016.01.011. Epub 2016 Feb 11.

PMID:
26877075
18.

Numerical characterization of DNA sequences based on the k-step Markov chain transition probability.

Dai Q, Liu XQ, Wang TM.

J Comput Chem. 2006 Nov 30;27(15):1830-42.

PMID:
16981233
19.
20.

Cell speed is independent of force in a mathematical model of amoeboidal cell motion with random switching terms.

Dallon JC, Evans EJ, Grant CP, Smith WV.

Math Biosci. 2013 Nov;246(1):1-7. doi: 10.1016/j.mbs.2013.09.005. Epub 2013 Sep 20.

PMID:
24060706

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