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Items: 1 to 20 of 101

1.

Integrative Proteo-genomic Analysis to Construct CNA-protein Regulatory Map in Breast and Ovarian Tumors.

Ma W, Chen LS, Özbek U, Han SW, Lin C, Paulovich AG, Zhong H, Wang P.

Mol Cell Proteomics. 2019 Aug 9;18(8 suppl 1):S66-S81. doi: 10.1074/mcp.RA118.001229. Epub 2019 Jul 7.

2.

Characterizing functional consequences of DNA copy number alterations in breast and ovarian tumors by spaceMap.

Conley CJ, Ozbek U, Wang P, Peng J.

J Genet Genomics. 2018 Jul 20;45(7):361-371. doi: 10.1016/j.jgg.2018.07.003. Epub 2018 Jul 26.

PMID:
30057342
3.

Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis.

Song X, Ji J, Gleason KJ, Yang F, Martignetti JA, Chen LS, Wang P.

Mol Cell Proteomics. 2019 Aug 9;18(8 suppl 1):S52-S65. doi: 10.1074/mcp.RA118.001220. Epub 2019 Jun 21.

4.

Integration and Analysis of CPTAC Proteomics Data in the Context of Cancer Genomics in the cBioPortal.

Wu P, Heins ZJ, Muller JT, Katsnelson L, de Bruijn I, Abeshouse AA, Schultz N, Fenyö D, Gao J.

Mol Cell Proteomics. 2019 Sep;18(9):1893-1898. doi: 10.1074/mcp.TIR119.001673. Epub 2019 Jul 15.

PMID:
31308250
5.

High-resolution analysis of copy number alterations and associated expression changes in ovarian tumors.

Haverty PM, Hon LS, Kaminker JS, Chant J, Zhang Z.

BMC Med Genomics. 2009 May 6;2:21. doi: 10.1186/1755-8794-2-21.

6.

Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingness.

Wang J, Wang P, Hedeker D, Chen LS.

Biostatistics. 2018 Jun 24. doi: 10.1093/biostatistics/kxy022. [Epub ahead of print]

PMID:
29939200
7.

Regularized Multivariate Regression for Identifying Master Predictors with Application to Integrative Genomics Study of Breast Cancer.

Peng J, Zhu J, Bergamaschi A, Han W, Noh DY, Pollack JR, Wang P.

Ann Appl Stat. 2010 Mar;4(1):53-77.

8.

A MIXED-EFFECTS MODEL FOR INCOMPLETE DATA FROM LABELING-BASED QUANTITATIVE PROTEOMICS EXPERIMENTS.

Chen LS, Wang J, Wang X, Wang P.

Ann Appl Stat. 2017 Mar;11(1):114-138. doi: 10.1214/16-AOAS994. Epub 2017 Apr 8.

9.

Specific genomic regions are differentially affected by copy number alterations across distinct cancer types, in aggregated cytogenetic data.

Kumar N, Cai H, von Mering C, Baudis M.

PLoS One. 2012;7(8):e43689. doi: 10.1371/journal.pone.0043689. Epub 2012 Aug 24.

10.

Integrated analysis of copy number alteration and RNA expression profiles of cancer using a high-resolution whole-genome oligonucleotide array.

Jung SH, Shin SH, Yim SH, Choi HS, Lee SH, Chung YJ.

Exp Mol Med. 2009 Jul 31;41(7):462-70. doi: 10.3858/emm.2009.41.7.051.

11.

Advanced Proteogenomic Analysis Reveals Multiple Peptide Mutations and Complex Immunoglobulin Peptides in Colon Cancer.

Woo S, Cha SW, Bonissone S, Na S, Tabb DL, Pevzner PA, Bafna V.

J Proteome Res. 2015 Sep 4;14(9):3555-67. doi: 10.1021/acs.jproteome.5b00264. Epub 2015 Jul 21.

12.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

Zhou Y, Wang P, Wang X, Zhu J, Song PX.

Genet Epidemiol. 2017 Jan;41(1):70-80. doi: 10.1002/gepi.22018. Epub 2016 Nov 10.

13.

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer.

Song E, Gao Y, Wu C, Shi T, Nie S, Fillmore TL, Schepmoes AA, Gritsenko MA, Qian WJ, Smith RD, Rodland KD, Liu T.

Sci Data. 2017 Jul 19;4:170091. doi: 10.1038/sdata.2017.91.

14.

Inferring gene regulatory relationships with a high-dimensional robust approach.

Zang Y, Zhao Q, Zhang Q, Li Y, Zhang S, Ma S.

Genet Epidemiol. 2017 Jul;41(5):437-454. doi: 10.1002/gepi.22047. Epub 2017 May 2.

15.

Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer.

Staaf J, Jönsson G, Ringnér M, Baldetorp B, Borg A.

Breast Cancer Res. 2011;13(6):R129. doi: 10.1186/bcr3075. Epub 2011 Dec 14.

16.

Computational identification of micro-structural variations and their proteogenomic consequences in cancer.

Lin YY, Gawronski A, Hach F, Li S, Numanagic I, Sarrafi I, Mishra S, McPherson A, Collins CC, Radovich M, Tang H, Sahinalp SC.

Bioinformatics. 2018 May 15;34(10):1672-1681. doi: 10.1093/bioinformatics/btx807.

17.

Conditional random pattern model for copy number aberration detection.

Li F, Zhou X, Huang W, Chang CC, Wong ST.

BMC Bioinformatics. 2010 Apr 22;11:200. doi: 10.1186/1471-2105-11-200.

18.

CDCOCA: a statistical method to define complexity dependence of co-occuring chromosomal aberrations.

Kumar N, Rehrauer H, Cai H, Baudis M.

BMC Med Genomics. 2011 Mar 3;4:21. doi: 10.1186/1755-8794-4-21.

19.

Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival.

Zhang L, Feizi N, Chi C, Hu P.

Front Genet. 2018 Oct 1;9:421. doi: 10.3389/fgene.2018.00421. eCollection 2018.

20.

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline.

Rudnick PA, Markey SP, Roth J, Mirokhin Y, Yan X, Tchekhovskoi DV, Edwards NJ, Thangudu RR, Ketchum KA, Kinsinger CR, Mesri M, Rodriguez H, Stein SE.

J Proteome Res. 2016 Mar 4;15(3):1023-32. doi: 10.1021/acs.jproteome.5b01091. Epub 2016 Feb 25.

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