Now showing items 1-5 of 5

    • Author correction: a robust benchmark for detection of germline large deletions and insertions (Nature Biotechnology, (2020), 38, 11, (1347-1355) 

      Zook, J. M.; Hansen, N. F.; Olson, N. D.; Chapman, L.; Mullikin, J. C.; Xiao, C.; Sherry, S.; Koren, S.; Phillippy, A. M.; Boutros, P. C.; Sahraeian, S. M. E.; Huang, V.; Rouette, A.; Alexander, N.; Mason, C. E.; Hajirasouliha, I.; Ricketts, C.; Lee, J.; Tearle, R.; Fiddes, I. T.; Barrio, A. M.; Wala, J.; Carroll, A.; Ghaffari, N.; Rodriguez, O. L.; Bashir, A.; Jackman, S.; Farrell, J. J.; Wenger, A. M.; Alkan, Can; Söylev, A.; Schatz, M. C.; Garg, S.; Church, G.; Marschall, T.; Chen, K.; Fan, X.; English, A. C.; Rosenfeld, J. A.; Zhou, w.; Zhou, W.; Mills, R. E.; Sage, J. M.; Davis, J. R.; Kaiser, M. D.; Oliver, J. S.; Catalano, A. P.; Chaisson, M. J. P.; Spies, N.; Sedlazeck, F. J.; Salit, M. (Nature Research, 2020)
    • The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: a collaborative cognitive and neuroimaging genetics project 

      Blokland, G. A. M.; Del Re, E. C.; Mesholam-Gately, R. I.; Jovicich, J.; Trampush, J. W.; Keshavan, M. S.; DeLisi, L. E.; Walters, J. T. R.; Turner, J. A.; Malhotra, A. K.; Lencz, T.; Shenton, M. E.; Voineskos, A. N.; Rujescu, D.; Giegling, I.; Kahn, R. S.; Roffman, J. L.; Holt, D. J.; Ehrlich, S.; Kikinis, Z.; Dazzan, P.; Murray, R. M.; Di Forti, M.; Lee, J.; Sim, K.; Lam, M.; Wolthusen, R. P. F.; De Zwarte, S. M. C.; Walton, E.; Cosgrove, D.; Kelly, S.; Maleki, N.; Osiecki, L.; Picchioni, M. M.; Bramon, E.; Russo, M.; David, A. S.; Mondelli, V.; Reinders, A. A. T. S.; Falcone, M. A.; Hartmann, A. M.; Konte, B.; Morris, D. W.; Gill, M.; Corvin, A. P.; Cahn, W.; Ho, N. F.; Liu, J. J.; Keefe, R. S. E.; Gollub, R. L.; Manoach, D. S.; Calhoun, V. D.; Schulz, S. C.; Sponheim, S. R.; Goff, D. C.; Buka, S. L.; Cherkerzian, S.; Thermenos, H. W.; Kubicki, M.; Nestor, P. G.; Dickie, E. W.; Vassos, E.; Ciufolini, S.; Marques, T. R.; Crossley, N. A.; Purcell, S. M.; Smoller, J. W.; Van Haren, N. E. M.; Toulopoulou, Timothea; Donohoe, G.; Goldstein, J. M.; Seidman, L. J.; McCarley, R. W.; Petryshen, T. L. (Elsevier, 2018)
      Background: Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia ...
    • Representing the Zoo World and the Traffic World in the language of the Causal Calculator 

      Akman, V.; Erdoğan, S. T.; Lee, J.; Lifschitz, V.; Turner, H. (Elsevier, 2004-03)
      The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCALC) is a system that answers queries about action domains described in a ...
    • A robust benchmark for detection of germline large deletions and insertions 

      Zook, J. M.; Hansen, N. F.; Olson, N. D.; Chapman, L.; Mullikin, J. C.; Xiao, C.; Sherry, S.; Koren, S.; Phillippy, A. M.; Boutros, P. C.; Sahraeian, S. M. E.; Huang, V.; Rouette, A.; Alexander, N.; Mason, C. E.; Hajirasouliha, I.; Ricketts, C.; Lee, J.; Tearle, R.; Fiddes, I. T.; Barrio, A. M.; Wala, J.; Carroll, A.; Ghaffari, N.; Rodriguez, O. L.; Bashir, A.; Jackman, S.; Farrell, J. J.; Wenger, A. M.; Alkan, Can; Söylev, A.; Schatz, M. C.; Garg, S.; Church, G.; Marschall, T.; Chen, K.; Fan, X.; English, A. C.; Rosenfeld, J. A.; Zhou, W.; Mills, R. E.; Sage, J. M.; Davis, J. R.; Kaiser, M. D.; Oliver, J. S.; Catalano, A. P.; Chaisson, M. J. P.; Spies, N.; Sedlazeck, F. J.; Salit, M. (Nature Research, 2020)
      New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and ...
    • SNR dependence of optimal parameters for apparent diffusion coefficient measurements 

      Sarıtaş, Emine Ülkü; Lee, J.; Nishimura, D. (IEEE, 2011)
      Optimizing the diffusion-weighted imaging (DWI) parameters (i.e., the b -value and the number of image averages) to the tissue of interest is essential for producing high-quality apparent diffusion coefficient (ADC) maps. ...