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Sarwal Lab »  Lab Members »  Postdoctoral Fellows »  Silvia Pineda, Ph.D.
Silvia Pineda, Ph.D.

Silvia Pineda, Ph.D.

Postdoctoral Fellow

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  • Zaragoza University, Spain, B.S., Statistics, 2006
  • Madrid Complutense University, Spain, M.S., Statistics, 2009
  • Madrid Autónoma University, Spain, M.S., Quantitative Methods in Epidemiology, 2012
  • University of Liege, Belgium Ph.D., System and Modeling Unit, 2015
  • National Cancer Research Centre Ph.D., Genetic and Molecular Epidemiology , 2015

I am currently a Post Doctoral fellow for the Sarwal lab (Department of Surgery at UCSF) and the Sirota lab (Computational Health Science at UCSF) working on kidney organ transplantation. I completed my PhD in Statistical Genetics at the Spanish National Cancer Research Centre in Spain jointly with the University of Liege in Belgium. 

  • Statistics Degree National Award, Ministry of Education and Science, Spain, 2006
  • Extraordinary Award for Statistics Degree, Zaragoza University, Spain, 2006

My work is focused on the development and application of advanced statistical methods for the integration of omics data. My research interest is based on the development of advanced statistical approaches to integrate omics and clinical/epidemiological data to better understand complex diseases. Now, I am involved in the analysis of Next Generation Sequencing data to better explain the rejection process of kidney transplants.

Most recent publications from a total of 11
  1. Pineda S, Sigdel TK, Chen J, Jackson AM, Sirota M, Sarwal MM. Novel Non-Histocompatibility Antigen Mismatched Variants Improve the Ability to Predict Antibody-Mediated Rejection Risk in Kidney Transplant. Front Immunol. 2017; 8:1687. View in PubMed
  2. Pineda S, Van Steen K, Malats N. Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer. Genet Epidemiol. 2017 09; 41(6):567-573. View in PubMed
  3. López de Maturana E, Pineda S, Brand A, Van Steen K, Malats N. Toward the integration of Omics data in epidemiological studies: still a "long and winding road". Genet Epidemiol. 2016 11; 40(7):558-569. View in PubMed
  4. Pineda S, Real FX, Kogevinas M, Carrato A, Chanock SJ, Malats N, Van Steen K. Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer. PLoS Genet. 2015 Dec; 11(12):e1005689. View in PubMed
  5. Mason-Lecomte A, Lopez de Maturana E, Pineda S, Rava M, Vordos D, Allory Y, Real F, Malats N. [Not Available]. Prog Urol. 2015 Nov; 25(13):758-9. View in PubMed
  6. Pineda S, Gomez-Rubio P, Picornell A, Bessonov K, Márquez M, Kogevinas M, Real FX, Van Steen K, Malats N. Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases. Hum Hered. 2015; 79(3-4):124-36. View in PubMed
  7. 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. Genetic variation in the TP53 pathway and bladder cancer risk. a comprehensive analysis. PLoS One. 2014; 9(5):e89952. View in PubMed
  8. Agarwal D, Pineda S, Michailidou K, Herranz J, Pita G, Moreno LT, Alonso MR, Dennis J, Wang Q, Bolla MK, Meyer KB, Menéndez-Rodríguez P, Hardisson D, Mendiola M, González-Neira A, Lindblom A, Margolin S, Swerdlow A, Ashworth A, Orr N, Jones M, Matsuo K, Ito H, Iwata H, Kondo N. FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium. Br J Cancer. 2014 Feb 18; 110(4):1088-100. View in PubMed
  9. Lundgren K, Brown M, Pineda S, Cuzick J, Salter J, Zabaglo L, Howell A, Dowsett M, Landberg G. Effects of cyclin D1 gene amplification and protein expression on time to recurrence in postmenopausal breast cancer patients treated with anastrozole or tamoxifen: a TransATAC study. Breast Cancer Res. 2012 Apr 04; 14(2):R57. View in PubMed
  10. Cuzick J, Dowsett M, Pineda S, Wale C, Salter J, Quinn E, Zabaglo L, Mallon E, Green AR, Ellis IO, Howell A, Buzdar AU, Forbes JF. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol. 2011 Nov 10; 29(32):4273-8. View in PubMed
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