Your browser doesn't support javascript.
loading
Synthetic lethality-based prediction of anti-SARS-CoV-2 targets.
Pal, Lipika R; Cheng, Kuoyuan; Nair, Nishanth Ulhas; Martin-Sancho, Laura; Sinha, Sanju; Pu, Yuan; Riva, Laura; Yin, Xin; Schischlik, Fiorella; Lee, Joo Sang; Chanda, Sumit K; Ruppin, Eytan.
  • Pal LR; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Cheng K; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Nair NU; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.
  • Martin-Sancho L; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Sinha S; Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Pu Y; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Riva L; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.
  • Yin X; Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Schischlik F; Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Lee JS; Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Chanda SK; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Ruppin E; Cancer Data Science Laboratory (CDSL), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
bioRxiv ; 2021 Sep 15.
Article en En | MEDLINE | ID: mdl-34545363
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article