Center-Authored Papers

Filters: Author is Margolin, Adam A  [Clear All Filters]
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Moser R, Xu C, Kao M, Annis J, Lerma LA, Schaupp CM, Gurley KE, Jang IS, Biktasova A, Yarbrough WG et al..  2014.  Functional kinomics identifies candidate therapeutic targets in head and neck cancer.. Clinical cancer research : an official journal of the American Association for Cancer Research. 20(16):4274-88. Abstract
Xu C, Nikolova O, Basom R, Mitchell RM, Shaw R, Moser R, Park H, Gurley KE, Kao M, Green CL et al..  2018.  Functional precision medicine identifies novel druggable targets and therapeutic options in head and neck cancer.. Clinical cancer research : an official journal of the American Association for Cancer Research. 24(12):2828-2843. Abstract
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Bilal E, Dutkowski J, Guinney J, Jang IS, Logsdon BA, Pandey G, Sauerwine BA, Shimoni Y, Moen Vollan HK, Mecham BH et al..  2013.  Improving breast cancer survival analysis through competition-based multidimensional modeling.. PLoS computational biology. 9(5):e1003047. Abstract
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Sperber H, Mathieu J, Wang Y, Ferreccio A, Hesson J, Xu Z, Fischer KA, Devi A, Detraux D, Gu H et al..  2015.  The metabolome regulates the epigenetic landscape during naive-to-primed human embryonic stem cell transition.. Nature cell biology. 17(12):1523-1535. Abstract
Nikolova O, Moser R, Kemp C, Gönen M, Margolin AA.  2017.  Modeling Gene-Wise Dependencies Improves the Identification of Drug Response Biomarkers in Cancer Studies.. Bioinformatics (Oxford, England). Abstract
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Paten B, Diekhans M, Druker BJ, Friend S, Guinney J, Gassner N, Guttman M, James Kent W, Mantey P, Margolin AA et al..  2015.  The NIH BD2K center for big data in translational genomics.. Journal of the American Medical Informatics Association : JAMIA. Abstract
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Davis RJ, Gönen M, Margineantu DH, Handeli S, Swanger J, Hoellerbauer P, Paddison PJ, Gu H, Raftery D, Grim JE et al..  2018.  Pan-cancer transcriptional signatures predictive of oncogenic mutations reveal that Fbw7 regulates cancer cell oxidative metabolism.. Proceedings of the National Academy of Sciences of the United States of America. 115(21):5462-5467. Abstract
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Gerhard DS, Clemons PA, Shamji AF, Hon C, Wagner BK, Schreiber SL, Krasnitz A, Sordella R, Sander C, Lowe SW et al..  2016.  Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance.. Molecular cancer research : MCR. Abstract