drexplorer: A tool to explore dose–response relationships and drug–drug interactions | Zendy

Pan Tong | Zendy; Kevin R. Coombes | Zendy; Faye M. Johnson | Zendy; Lauren A. Byers | Zendy; Lixia Diao | Zendy; Diane D. Liu | Zendy; J. Jack Lee | Zendy; John V. Heymach | Zendy; Jing Wang | Zendy

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drexplorer: A tool to explore dose–response relationships and drug–drug interactions

Author(s) -

Pan Tong,

Kevin R. Coombes,

Faye M. Johnson,

Lauren A. Byers,

Lixia Diao,

Diane D. Liu,

J. Jack Lee,

John V. Heymach,

Jing Wang

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv028

Subject(s) - replicate , computer science , drug response , graphical user interface , interface (matter) , software , outlier , data mining , r package , drug , computation , programming language , artificial intelligence , statistics , medicine , operating system , pharmacology , mathematics , bubble , maximum bubble pressure method

Nonlinear dose-response models are primary tools for estimating the potency [e.g. half-maximum inhibitory concentration (IC) known as IC50] of anti-cancer drugs. We present drexplorer software, which enables biologists to evaluate replicate reproducibility, detect outlier data points, fit different models, select the best model, estimate IC values at different percentiles and assess drug-drug interactions. drexplorer serves as a computation engine within the R environment and a graphical interface for users who do not have programming backgrounds.

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