Adam A. Margolin, Ph.D.

Oregon Health and Science University, Portland, OR 
Cancer, Gene regulatory models, Computational Biology
"Adam Margolin"


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Andrea Califano grad student 2008 Columbia (Physics Tree)
 (Computational inference of genetic regulatory networks in human cancer cells.)
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Lee AY, Ewing AD, Ellrott K, et al. (2018) Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection. Genome Biology. 19: 188
Xu C, Nikolova O, Basom R, 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
Gönen M, Weir BA, Cowley GS, et al. (2017) A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines. Cell Systems
Gerhard DS, Clemons PA, Shamji AF, et al. (2016) Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance. Molecular Cancer Research : McR
Sperber H, Mathieu J, Wang Y, et al. (2015) The metabolome regulates the epigenetic landscape during naive-to-primed human embryonic stem cell transition. Nature Cell Biology
Paten B, Diekhans M, Druker BJ, et al. (2015) The NIH BD2K center for big data in translational genomics. Journal of the American Medical Informatics Association : Jamia
Ewing AD, Houlahan KE, Hu Y, et al. (2015) Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. Nature Methods
Jang IS, Dienstmann R, Margolin AA, et al. (2015) Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 32-43
Boutros PC, Margolin AA, Stuart JM, et al. (2014) Toward better benchmarking: challenge-based methods assessment in cancer genomics. Genome Biology. 15: 462
Chaibub Neto E, Bare JC, Margolin AA. (2014) Simulation studies as designed experiments: the comparison of penalized regression models in the "large p, small n" setting. Plos One. 9: e107957
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