Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model
出版年份 2019 全文链接
标题
Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model
作者
关键词
Anticancer drug response, Cell line-drug complex network, Computational prediction model, Cell line, Precision medicine
出版物
BMC BIOINFORMATICS
Volume 20, Issue 1, Pages -
出版商
Springer Nature
发表日期
2019-01-23
DOI
10.1186/s12859-019-2608-9
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Drug Response Prediction as a Link Prediction Problem
- (2017) Zachary Stanfield et al. Scientific Reports
- Genome and network visualization facilitates the analyses of the effects of drugs and mutations on protein-protein and drug-protein networks
- (2016) Arnaud Céol et al. BMC BIOINFORMATICS
- Nearest neighbor imputation algorithms: a critical evaluation
- (2016) Lorenzo Beretta et al. BMC Medical Informatics and Decision Making
- Predicting response to multidrug regimens in cancer patients using cell line experiments and regularised regression models
- (2015) Steffen Falgreen et al. BMC CANCER
- Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection
- (2015) Zuoli Dong et al. BMC CANCER
- Health: Make precision medicine work for cancer care
- (2015) Mark A. Rubin NATURE
- Ten things we have to do to achieve precision medicine
- (2015) I. S. Kohane SCIENCE
- Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients
- (2015) D. Fey et al. Science Signaling
- Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model
- (2015) Naiqian Zhang et al. PLoS Computational Biology
- Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients
- (2015) D. Fey et al. Science Signaling
- A p-Median approach for predicting drug response in tumour cells
- (2014) Elisabetta Fersini et al. BMC BIOINFORMATICS
- A community effort to assess and improve drug sensitivity prediction algorithms
- (2014) James C Costello et al. NATURE BIOTECHNOLOGY
- Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines
- (2014) Paul Geeleher et al. GENOME BIOLOGY
- Inconsistency in large pharmacogenomic studies
- (2013) Benjamin Haibe-Kains et al. NATURE
- Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
- (2013) Michael P. Menden et al. PLoS One
- Prediction Errors in Learning Drug Response from Gene Expression Data – Influence of Labeling, Sample Size, and Machine Learning Algorithm
- (2013) Immanuel Bayer et al. PLoS One
- Profiles of Basal and Stimulated Receptor Signaling Networks Predict Drug Response in Breast Cancer Lines
- (2013) M. Niepel et al. Science Signaling
- Modeling precision treatment of breast cancer
- (2013) Anneleen Daemen et al. GENOME BIOLOGY
- Systematic identification of genomic markers of drug sensitivity in cancer cells
- (2012) Mathew J. Garnett et al. NATURE
- The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
- (2012) Jordi Barretina et al. NATURE
- Building the process-drug–side effect network to discover the relationship between biological Processes and side effects
- (2011) Sejoon Lee et al. BMC BIOINFORMATICS
- Open Babel: An open chemical toolbox
- (2011) Noel M O'Boyle et al. Journal of Cheminformatics
- Structural similarity assessment for drug sensitivity prediction in cancer
- (2009) Pavithra Shivakumar et al. BMC BIOINFORMATICS
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