Similar articles for PMID: 19963359

Year	Number of Results
1990	1
1998	1
1999	2
2000	3
2001	2
2002	6
2003	4
2004	7
2005	7
2006	8
2007	14
2008	17
2009	43
2010	70
2011	46
2012	41
2013	34
2014	28
2015	21
2016	30
2017	11
2018	16
2019	25
2020	7
2021	5
2022	2
2024	0

1

A new multiple regression approach for the construction of genetic regulatory networks.

Zhang SQ, Ching WK, Tsing NK, Leung HY, Guo D. Zhang SQ, et al. Artif Intell Med. 2010 Feb-Mar;48(2-3):153-60. doi: 10.1016/j.artmed.2009.11.001. Epub 2009 Dec 5. Artif Intell Med. 2010. PMID: 19963359

2

Mixture classification model based on clinical markers for breast cancer prognosis.

Zeng T, Liu J. Zeng T, et al. Artif Intell Med. 2010 Feb-Mar;48(2-3):129-37. doi: 10.1016/j.artmed.2009.07.008. Epub 2009 Dec 14. Artif Intell Med. 2010. PMID: 20005686

3

Reconstruction of transcriptional network from microarray data using combined mutual information and network-assisted regression.

Wang XD, Qi YX, Jiang ZL. Wang XD, et al. IET Syst Biol. 2011 Mar;5(2):95-102. doi: 10.1049/iet-syb.2010.0041. IET Syst Biol. 2011. PMID: 21405197 Free article.

4

Gene expression complex networks: synthesis, identification, and analysis.

Lopes FM, Cesar RM, Costa Lda F. Lopes FM, et al. J Comput Biol. 2011 Oct;18(10):1353-67. doi: 10.1089/cmb.2010.0118. Epub 2011 May 6. J Comput Biol. 2011. PMID: 21548810

5

EXAMINE: a computational approach to reconstructing gene regulatory networks.

Deng X, Geng H, Ali H. Deng X, et al. Biosystems. 2005 Aug;81(2):125-36. doi: 10.1016/j.biosystems.2005.02.007. Biosystems. 2005. PMID: 15951103

6

Neural networks.

Yang ZR. Yang ZR. Methods Mol Biol. 2010;609:197-222. doi: 10.1007/978-1-60327-241-4_12. Methods Mol Biol. 2010. PMID: 20221921

7

Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data.

Kim S, Imoto S, Miyano S. Kim S, et al. Biosystems. 2004 Jul;75(1-3):57-65. doi: 10.1016/j.biosystems.2004.03.004. Biosystems. 2004. PMID: 15245804

8

Inferring gene regulatory networks by integrating static and dynamic data.

Ferrazzi F, Magni P, Sacchi L, Nuzzo A, Petrovic U, Bellazzi R. Ferrazzi F, et al. Int J Med Inform. 2007 Dec;76 Suppl 3:S462-75. doi: 10.1016/j.ijmedinf.2007.07.005. Epub 2007 Sep 6. Int J Med Inform. 2007. PMID: 17825607

9

Modeling of gene regulatory network dynamics using threshold logic.

Gowda T, Vrudhula S, Kim S. Gowda T, et al. Ann N Y Acad Sci. 2009 Mar;1158:71-81. doi: 10.1111/j.1749-6632.2008.03754.x. Ann N Y Acad Sci. 2009. PMID: 19348633

10

Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data.

Kim J, Bates DG, Postlethwaite I, Heslop-Harrison P, Cho KH. Kim J, et al. Bioinformatics. 2008 May 15;24(10):1286-92. doi: 10.1093/bioinformatics/btn107. Epub 2008 Mar 26. Bioinformatics. 2008. PMID: 18367478

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