Svitlana Tyekucheva

Research Scientist
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Research

My statistical research interests lie in developing new, and tailoring existing statistical methods to efficiently process and analyze high-dimensional genomic data. In particular, my areas of interest include applications of dimension reduction, resampling methods, supervised and unsupervised classification, and regression techniques applied to the data arising from cancer studies.  I am interested in methods for all stages of high-throughput data lifecycle: starting from preprocessing and ending with the integrated inference across different studies and data types. My latest interests include analyzing nextgen sequencing and metabolomics data. My research work in statistics and bioinformatics is largely inspired by collaborations with both basic scientists and clinicians.

 

Biography


 

Recent Publications

Ganzfried BF, Riester M, Haibe-Kains B, Risch T, Tyekucheva S, Jazic I, Wang XV, Ahmadifar M, Birrer MJ, Parmigiani G, Huttenhower C, Waldron L. curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome. Database (Oxford). 2013; 2013:bat013.

 

Li Q, Seo JH, Stranger B, McKenna A, Pe'er I, Laframboise T, Brown M, Tyekucheva S, Freedman ML. Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci. Cell. 2013 Jan 31; 152(3):633-41.

 

Tyekucheva S, Marchionni L, Karchin R, Parmigiani G. Integrating diverse genomic data using gene sets. Genome Biol. 2011; 12(10):R105.

 

Tyekucheva S, Yolken RH, McCombie WR, Parla J, Kramer M, Wheelan SJ, Sabunciyan S. Establishing the baseline level of repetitive element expression in the human cortex. BMC Genomics. 2011; 12:495.

 

Carter H, Chen S, Isik L, Tyekucheva S, Velculescu VE, Kinzler KW, Vogelstein B, Karchin R. Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations. Cancer Res. 2009 Aug 15; 69(16):6660-7.

 

Tyekucheva S, Makova KD, Karro JE, Hardison RC, Miller W, Chiaromonte F. Human-macaque comparisons illuminate variation in neutral substitution rates. Genome Biol. 2008; 9(4):R76.

 

Kelkar YD, Tyekucheva S, Chiaromonte F, Makova KD. The genome-wide determinants of human and chimpanzee microsatellite evolution. Genome Res. 2008 Jan; 18(1):30-8.

 

Miller W, Rosenbloom K, Hardison RC, Hou M, Taylor J, Raney B, Burhans R, King DC, Baertsch R, Blankenberg D, Kosakovsky Pond SL, Nekrutenko A, Giardine B, Harris RS, Tyekucheva S, Diekhans M, Pringle TH, Murphy WJ, Lesk A, Weinstock GM, Lindblad-Toh K, Gibbs RA, Lander ES, Siepel A, Haussler D, Kent WJ. 28-way vertebrate alignment and conservation track in the UCSC Genome Browser. Genome Res. 2007 Dec; 17(12):1797-808.

 

Kvikstad EM, Tyekucheva S, Chiaromonte F, Makova KD. A macaque's-eye view of human insertions and deletions: differences in mechanisms. PLoS Comput Biol. 2007 Sep; 3(9):1772-82.

 

Taylor J, Tyekucheva S, King DC, Hardison RC, Miller W, Chiaromonte F. ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements. Genome Res. 2006 Dec; 16(12):1596-604.


 

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