Additional file 7: of Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  • Noah Berlow (Creator)
  • Rishi Rikhi (Contributor)
  • Mathew Geltzeiler (Creator)
  • Jinu Abraham (Contributor)
  • Matthew N. Svalina (Creator)
  • Lara E. Davis (Creator)
  • Erin Wise (Creator)
  • Maria Mancini (Creator)
  • Jonathan Noujaim (Creator)
  • Atiya Mansoor (Contributor)
  • Michael J. Quist (Creator)
  • Kevin L. Matlock (Creator)
  • Martin W. Goros (Creator)
  • Brian S. Hernandez (Creator)
  • Yee C. Doung (Creator)
  • Khin Thway (Contributor)
  • Tomohide Tsukahara (Contributor)
  • Jun Nishio (Creator)
  • Elaine T. Huang (Creator)
  • Susan Airhart (Creator)
  • Carol J. Bult (Creator)
  • Regina Gandour-Edwards (Creator)
  • Robert G. Maki (Creator)
  • Robin L. Jones (Creator)
  • Joel E Michalek (Creator)
  • Milan Milovancev (Creator)
  • Souparno Ghosh (Contributor)
  • Ranadip Pal (Contributor)
  • Charles Keller (Creator)
  • Elaine C. Huang Huang (Creator)
  • Robin L. Jones (Creator)

Dataset

Description

Figure S7. Probabilistic Target Inhibition Map (PTIM) model of U23674 Roche chemical screen hits. Values in the center of PTIM blocks represent expected scaled sensitivity following inhibition of associated block targets. (A) Base chemical screen informed PTIM. (B) RNA-seqâ +â chemical screen informed PTIM. Roche screen hits include CDK2 inhibitors. However, no CDK inhibitor was a known inhibitor of non-CDK targets, limiting development of personalized combinations involving CDK inhibitors. (TIF 29510 kb)
Date made available2019
PublisherFigshare

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