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Items: 12

1.

Challenges in the Integration of Omics and Non-Omics Data.

López de Maturana E, Alonso L, Alarcón P, Martín-Antoniano IA, Pineda S, Piorno L, Calle ML, Malats N.

Genes (Basel). 2019 Mar 20;10(3). pii: E238. doi: 10.3390/genes10030238. Review.

2.

Bladder Cancer Genetic Susceptibility. A Systematic Review.

de Maturana EL, Rava M, Anumudu C, Sáez O, Alonso D, Malats N.

Bladder Cancer. 2018 Apr 26;4(2):215-226. doi: 10.3233/BLC-170159.

3.

DoriTool: A Bioinformatics Integrative Tool for Post-Association Functional Annotation.

Martín-Antoniano I, Alonso L, Madrid M, López de Maturana E, Malats N.

Public Health Genomics. 2017;20(2):126-135. doi: 10.1159/000477561. Epub 2017 Jul 13.

PMID:
28700989
4.

Toward the integration of Omics data in epidemiological studies: still a "long and winding road".

López de Maturana E, Pineda S, Brand A, Van Steen K, Malats N.

Genet Epidemiol. 2016 Nov;40(7):558-569. doi: 10.1002/gepi.21992. Epub 2016 Jul 18.

PMID:
27432111
5.

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

Masson-Lecomte A, López de Maturana E, Goddard ME, Picornell A, Rava M, González-Neira A, Márquez M, Carrato A, Tardon A, Lloreta J, Garcia-Closas M, Silverman D, Rothman N, Kogevinas M, Allory Y, Chanock SJ, Real FX, Malats N; SBC/EPICURO Study Investigators.

Cancer Epidemiol Biomarkers Prev. 2016 Jul;25(7):1144-50. doi: 10.1158/1055-9965.EPI-15-0894. Epub 2016 May 6.

6.

Next generation modeling in GWAS: comparing different genetic architectures.

López de Maturana E, Ibáñez-Escriche N, González-Recio Ó, Marenne G, Mehrban H, Chanock SJ, Goddard ME, Malats N.

Hum Genet. 2014 Oct;133(10):1235-53. doi: 10.1007/s00439-014-1461-1. Epub 2014 Jun 17.

PMID:
24934831
7.

Genetic variation in the TP53 pathway and bladder cancer risk. a comprehensive analysis.

Pineda S, Milne RL, Calle ML, Rothman N, López de Maturana E, Herranz J, Kogevinas M, Chanock SJ, Tardón A, Márquez M, Guey LT, García-Closas M, Lloreta J, Baum E, González-Neira A, Carrato A, Navarro A, Silverman DT, Real FX, Malats N.

PLoS One. 2014 May 12;9(5):e89952. doi: 10.1371/journal.pone.0089952. eCollection 2014.

8.

Whole genome prediction of bladder cancer risk with the Bayesian LASSO.

de Maturana EL, Chanok SJ, Picornell AC, Rothman N, Herranz J, Calle ML, García-Closas M, Marenne G, Brand A, Tardón A, Carrato A, Silverman DT, Kogevinas M, Gianola D, Real FX, Malats N.

Genet Epidemiol. 2014 Jul;38(5):467-76. doi: 10.1002/gepi.21809. Epub 2014 May 5.

PMID:
24796258
9.

Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.

de Maturana EL, Ye Y, Calle ML, Rothman N, Urrea V, Kogevinas M, Petrus S, Chanock SJ, Tardón A, García-Closas M, González-Neira A, Vellalta G, Carrato A, Navarro A, Lorente-Galdós B, Silverman DT, Real FX, Wu X, Malats N.

PLoS One. 2013 Dec 31;8(12):e83745. doi: 10.1371/journal.pone.0083745. eCollection 2013.

10.

Modeling relationships between calving traits: a comparison between standard and recursive mixed models.

de Maturana EL, de los Campos G, Wu XL, Gianola D, Weigel KA, Rosa GJ.

Genet Sel Evol. 2010 Jan 25;42:1. doi: 10.1186/1297-9686-42-1.

12.

Exploring biological relationships between calving traits in primiparous cattle with a Bayesian recursive model.

de Maturana EL, Wu XL, Gianola D, Weigel KA, Rosa GJ.

Genetics. 2009 Jan;181(1):277-87. doi: 10.1534/genetics.108.094888. Epub 2008 Nov 3.

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