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Incorporating existing network information into gene network inference.

Christley S, Nie Q, Xie X.

PLoS One. 2009 Aug 27;4(8):e6799. doi: 10.1371/journal.pone.0006799.


Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods.

Qin J, Hu Y, Xu F, Yalamanchili HK, Wang J.

Methods. 2014 Jun 1;67(3):294-303. doi: 10.1016/j.ymeth.2014.03.006. Epub 2014 Mar 17.


Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

Jia B, Wang X.

EURASIP J Bioinform Syst Biol. 2013 Dec 17;2013(1):16. doi: 10.1186/1687-4153-2013-16.


Inference of gene regulatory networks incorporating multi-source biological knowledge via a state space model with L1 regularization.

Hasegawa T, Yamaguchi R, Nagasaki M, Miyano S, Imoto S.

PLoS One. 2014 Aug 27;9(8):e105942. doi: 10.1371/journal.pone.0105942. eCollection 2014.


Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

Gong W, Koyano-Nakagawa N, Li T, Garry DJ.

BMC Bioinformatics. 2015 Mar 7;16:74. doi: 10.1186/s12859-015-0460-0.


Sets2Networks: network inference from repeated observations of sets.

Clark NR, Dannenfelser R, Tan CM, Komosinski ME, Ma'ayan A.

BMC Syst Biol. 2012 Jul 23;6:89. doi: 10.1186/1752-0509-6-89.


Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities.

Sanguinetti G, Lawrence ND, Rattray M.

Bioinformatics. 2006 Nov 15;22(22):2775-81. Epub 2006 Sep 11.


Network enrichment analysis in complex experiments.

Shojaie A, Michailidis G.

Stat Appl Genet Mol Biol. 2010;9:Article22. doi: 10.2202/1544-6115.1483. Epub 2010 May 22.


An algebra-based method for inferring gene regulatory networks.

Vera-Licona P, Jarrah A, Garcia-Puente LD, McGee J, Laubenbacher R.

BMC Syst Biol. 2014 Mar 26;8:37. doi: 10.1186/1752-0509-8-37.


Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

Marbach D, Roy S, Ay F, Meyer PE, Candeias R, Kahveci T, Bristow CA, Kellis M.

Genome Res. 2012 Jul;22(7):1334-49. doi: 10.1101/gr.127191.111. Epub 2012 Mar 28.


Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila.

Joshi A, Beck Y, Michoel T.

J Comput Biol. 2015 Apr;22(4):253-65. doi: 10.1089/cmb.2014.0290.


Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns.

Zheng Z, Christley S, Chiu WT, Blitz IL, Xie X, Cho KW, Nie Q.

BMC Syst Biol. 2014 Jan 8;8:3. doi: 10.1186/1752-0509-8-3.


A computational framework for gene regulatory network inference that combines multiple methods and datasets.

Gupta R, Stincone A, Antczak P, Durant S, Bicknell R, Bikfalvi A, Falciani F.

BMC Syst Biol. 2011 Apr 13;5:52. doi: 10.1186/1752-0509-5-52.


A probabilistic approach to learn chromatin architecture and accurate inference of the NF-κB/RelA regulatory network using ChIP-Seq.

Yang J, Mitra A, Dojer N, Fu S, Rowicka M, Brasier AR.

Nucleic Acids Res. 2013 Aug;41(15):7240-59. doi: 10.1093/nar/gkt493. Epub 2013 Jun 14.


Optimal sparsity criteria for network inference.

Tjärnberg A, Nordling TE, Studham M, Sonnhammer EL.

J Comput Biol. 2013 May;20(5):398-408. doi: 10.1089/cmb.2012.0268.


iRegulon: from a gene list to a gene regulatory network using large motif and track collections.

Janky R, Verfaillie A, Imrichová H, Van de Sande B, Standaert L, Christiaens V, Hulselmans G, Herten K, Naval Sanchez M, Potier D, Svetlichnyy D, Kalender Atak Z, Fiers M, Marine JC, Aerts S.

PLoS Comput Biol. 2014 Jul 24;10(7):e1003731. doi: 10.1371/journal.pcbi.1003731. eCollection 2014 Jul.


Using directed information to build biologically relevant influence networks.

Rao A, Hero AO 3rd, States DJ, Engel JD.

J Bioinform Comput Biol. 2008 Jun;6(3):493-519.


Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data.

Gu F, Hsu HK, Hsu PY, Wu J, Ma Y, Parvin J, Huang TH, Jin VX.

BMC Syst Biol. 2010 Dec 17;4:170. doi: 10.1186/1752-0509-4-170.


Reverse engineering module networks by PSO-RNN hybrid modeling.

Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW.

BMC Genomics. 2009 Jul 7;10 Suppl 1:S15. doi: 10.1186/1471-2164-10-S1-S15.


Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison.

Titsias MK, Honkela A, Lawrence ND, Rattray M.

BMC Syst Biol. 2012 May 30;6:53. doi: 10.1186/1752-0509-6-53.

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