Computational modeling of ovarian cancer dynamics suggests optimal strategies for therapy and screening Article

Gu, Shengqing, Lheureux, Stephanie, Sayad, Azin et al. (2021). Computational modeling of ovarian cancer dynamics suggests optimal strategies for therapy and screening . PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 118(25), 10.1073/pnas.2026663118

Open Access International Collaboration

cited authors

  • Gu, Shengqing; Lheureux, Stephanie; Sayad, Azin; Cybulska, Paulina; Hogen, Liat; Vyarvelska, Iryna; Tu, Dongsheng; Parulekar, Wendy R; Nankivell, Matthew; Kehoe, Sean; Chi, Dennis S; Levine, Douglas A; Bernardini, Marcus Q; Rosen, Barry; Oza, Amit; Brown, Myles; Neel, Benjamin G

sustainable development goals

authors

publication date

  • June 22, 2021

published in

keywords

  • CELL-LINES
  • CISPLATIN RESISTANCE
  • DRUG-RESISTANCE
  • EVOLUTION
  • EXPRESSION
  • Multidisciplinary Sciences
  • NEOADJUVANT CHEMOTHERAPY
  • PERITONEAL CARCINOMA
  • PRIMARY DEBULKING SURGERY
  • SURGICAL CYTOREDUCTION
  • Science & Technology
  • Science & Technology - Other Topics
  • TIME-INTERVAL
  • computational
  • neoadjuvant chemotherapy
  • ovarian cancer
  • primary debunking surgery

Digital Object Identifier (DOI)

publisher

  • NATL ACAD SCIENCES

volume

  • 118

issue

  • 25