منابع مشابه
Predicting HIV drug resistance with neural networks
MOTIVATION Drug resistance is a very important factor influencing the failure of current HIV therapies. The ability to predict the drug resistance of HIV protease mutants may be useful in developing more effective and longer lasting treatment regimens. METHODS The HIV resistance is predicted to two current protease inhibitors, Indinavir and Saquinavir. The problem was approached from two pers...
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PURPOSE Accurate prediction of an individual patient's drug response is an important prerequisite of personalized medicine. Recent pharmacogenomics research in chemosensitivity prediction has studied the gene-drug correlation based on transcriptional profiling. However, proteomic profiling will more directly solve the current functional and pharmacologic problems. We sought to determine whether...
متن کاملPredicting cancer drug response: advancing the DREAM.
The DREAM challenge is a community effort to assess current capabilities in systems biology. Two recent challenges focus on cancer cell drug sensitivity and drug synergism, and highlight strengths and weaknesses of current approaches.
متن کاملMining complex genotypic features for predicting HIV-1 drug resistance
MOTIVATION Human immunodeficiency virus type 1 (HIV-1) evolves in human body, and its exposure to a drug often causes mutations that enhance the resistance against the drug. To design an effective pharmacotherapy for an individual patient, it is important to accurately predict the drug resistance based on genotype data. Notably, the resistance is not just the simple sum of the effects of all mu...
متن کاملMRBF: A Method for Predicting HIV-1 Drug Resistance
This paper presents the MRBF network, a new algorithm adapted from the RBF network, to construct the classifiers for predicting phenotypic resistance on 6 protease inhibitors. The performance of the prediction was measured by 10-fold cross-validation. The results show that MRBF gives the lowest average mean square error (MSE) when compared with the traditional RBF network and multiple linear re...
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ژورنال
عنوان ژورنال: Nature Reviews Genetics
سال: 2013
ISSN: 1471-0056,1471-0064
DOI: 10.1038/nrg3590