@inproceedings{b58726fd3ff544e4b55be2c935337d2c,
title = "Connecting clusters of patient to drug responses of cell lines to suggest personalized therapeutics for breast cancer",
abstract = "Recent surge in genome-wide expression data from patient tumors and cell-lines in breast cancer, as well as response data of breast cancer cell-lines to many drugs, opens the opportunity for data integration approaches that can lead to better personalized therapeutics. Here we integrated such data to generate a tripartite network that connects clusters of patients to cell-lines, and cell-lines to drugs to suggest which drugs may work best for each cluster of patients. We combined gene expression profiles from 400 patient tumor samples from two independent publicly-available studies, with gene expression and drug growth-inhibition-response profiles of 31 breast cancer cell-lines to build this tripartite network.",
keywords = "breast cancer, data integration, gene expression, molecular profiling, systems biology, systems pharmacology",
author = "Simon Gordonov and Avi Ma'Ayan",
year = "2012",
doi = "10.1109/BIBMW.2012.6470378",
language = "English",
isbn = "9781467327466",
series = "Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012",
pages = "529--534",
booktitle = "Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012",
note = "2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 ; Conference date: 04-10-2012 Through 07-10-2012",
}