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  1. 1.   Target identification among known drugs by deep learning from heterogeneous networks
  2. Zeng, Xiangxiang; Zhu, Siyi; Lu, Weiqiang; Liu, Zehui; Huang, Jin; Zhou, Yadi; Fang, Jiansong; Huang, Yin; Guo, Huimin; Li, Lang; Trapp, Bruce D.; Nussinov,Ruth; Eng, Charis; Loscalzo, Joseph; Cheng, Feixiong
  3. CHEMICAL SCIENCE. 2020, Feb 21; 11(7): 1775-1797.
  1. 2.   Sickle Cell Trait and the Risk of ESRD in Blacks
  2. Naik, Rakhi P.; Irvin, Marguerite R.; Judd, Suzanne; Gutierrez, Orlando M.; Zakai, Neil A.; Derebail, Vimal K.; Peralta, Carmen; Lewis, Michael R.; Zhi, Degui; Arnett, Donna; McClellan, William; Wilson, James G.; Reiner, Alexander P.; Kopp, Jeffrey B.; Winkler, Cheryl; Cushman, Mary
  3. Journal of the American Society of Nephrology. 2017, Jul 1; 28(7): 2180-2187.
  1. 3.   Polymorphisms in the Nonmuscle Myosin Heavy Chain 9 Gene (MYH9) Are Associated with Albuminuria in Hypertensive African Americans: The HyperGEN Study
  2. Freedman, B. I.; Kopp, J. B.; Winkler, C. A.; Nelson, G. W.; Rao, D. C.; Eckfeldt, J. H.; Leppert, M. F.; Hicks, P. J.; Divers, J.; Langefeld, C. D.; Hunt, S. C.
  3. American Journal of Nephrology. 2009 29(6): 626-632.
  1. 4.   Targeted disruption of Stat6 DNA binding activity by an oligonucleotide decoy blocks IL-4-driven T(H)2 cell response
  2. Wang, L. H.; Yang, X. Y.; Kirken, R. A.; Resau, J. H.; Farrar, W. L.
  3. Blood. 2000 95(4): 1249-1257.
  1. 5.   The promise of comparative genomics in mammals
  2. O'Brien, S. J.; Menotti-Raymond, M.; Murphy, W. J.; Nash, W. G.; Wienberg, J.; Stanyon, R.; Copeland, N. G.; Jenkins, N. A.; Womack, J. E.; Graves, J. A. M.
  3. Science. 1999 286(5439): 458-+.
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