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Updated: Apr 6, 2026

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
Published on: July 15, 2015
Improving Drug Sensitivity Prediction Using Different Types of Data
H A Hejase1, C Chan2
1Department of Computer Science and Engineering, Michigan State University East Lansing, Michigan, USA.
Abstract:
The algorithms and models used to address the two subchallenges that are part of the NCI-DREAM (Dialogue for Reverse Engineering Assessments and Methods) Drug Sensitivity Prediction Challenge (2012) are presented. In subchallenge 1, a bidirectional search algorithm is introduced and optimized using an ensemble scheme and a nonlinear support vector machine (SVM) is then applied to predict the effects of the drug compounds on breast cancer cell lines. In subchallenge 2, a weighted Euclidean distance method is introduced to predict and rank the drug combinations from the most to the least effective in reducing the viability of a diffuse large B-cell lymphoma (DLBCL) cell line.
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