Predictive modeling of anti-cancer drug sensitivity from genetic characterizations

Raziur Rahman, Ranadip Pal

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Accurately predicting sensitivity of tumor cells to anti-cancer drugs based on genetic characterizations is a significant challenge for personalized cancer therapy. This chapter provides a computational procedure to design predictive models from individual genomic characterizations and combine them to arrive at an integrated predictive model. Integrated modeling employs the complementary information from heterogeneous genetic characterizations to improve the prediction error as well as lowering the error confidence interval.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages227-241
Number of pages15
DOIs
StatePublished - 2019

Publication series

NameMethods in Molecular Biology
Volume1878
ISSN (Print)1064-3745

Keywords

  • Drug sensitivity prediction
  • Integrated genomic modeling
  • Random Forests

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