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  1. 1.   Learning curves for drug response prediction in cancer cell lines
  2. Partin, Alexander; Brettin, Thomas; Evrard,Yvonne; Zhu, Yitan; Yoo, Hyunseung; Xia, Fangfang; Jiang, Songhao; Clyde, Austin; Shukla, Maulik; Fonstein, Michael; Doroshow, James H.; Stevens, Rick L.
  3. BMC bioinformatics. 2021, May 17; 22(1):
  1. 2.   Power of Microbiome Beta-Diversity Analyses Based on Standard Reference Samples
  2. Gail, Mitchell H; Wan,Yunhu; Shi, Jianxin
  3. American journal of epidemiology. 2021, Mar; 190(3): 439-447.
  1. 3.   RNA2Drawer: Geometrically Strict Drawing of Nucleic Acid Structures with Graphical Structure Editing and Highlighting of Complementary Subsequences
  2. Johnson, Philip Z; Kasprzak,Wojciech; Shapiro,Bruce; Simon, Anne E
  3. RNA biology. 2019, Aug 26; 1-5.
  1. 4.   Systemic flaws cannot be fixed with minor tweaks
  2. Cuss, S. M.
  3. Proceedings of the National Academy of Sciences of the United States of America. 2014, 1-Jul; 111(26): E2635.
  1. 5.   Flux control and excess capacity in the enzymes of glycolysis and their relationship to flight metabolism in Drosophila melanogaster
  2. Eanes, W. F.; Merritt, T. J. S.; Flowers, J. M.; Kumagai, S.; Sezgin, E.; Zhu, C. T.
  3. Proceedings of the National Academy of Sciences of the United States of America. 2006, Dec; 103(51): 19413-19418.
  1. 6.   Ets1 oncogene induction by ELF-modulated 50 MHz radiofrequency electromagnetic field
  2. Romano-Spica, V.; Mucci, N.; Ursini, C. L.; Ianni, A.; Bhat, N. K.
  3. Bioelectromagnetics. 2000 21(1): 8-18.
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