1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Simultaneous inference of cell-line-specific gene regulatory networks and mode-of-action of drugs from drug-induced gene expression measurements
Paper ID : 1462-ICB10
Authors:
Mohammad Taheri-Ledari1, Amirali Zandieh2, Kaveh Kavousi *1, Sayed-Amir Marashi3
1Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
2Department of Biophysics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
3Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran
Abstract:
Personalized molecular networks help in elucidating drug resistance mechanisms, finding new therapeutic targets, and predicting the effectiveness of combination therapy. In this study a method for simultaneously inferring gene regulatory network and mode-of-action of drugs from gene expression measurements of drug-perturbed cancer cell-lines is proposed. An inferred model is a dynamic state-space representation whose variables are genes and inputs are drug dosages. Such a model includes gene-gene and drug-gene (mode-of-action) relationships. To implement the proposed method, drug-induced expression levels of nearly 1000 landmark genes for a set of cell-lines in the LINCS database were employed. Since no time-series gene expression data are available the cell-lines are assumed to be in steady-state. The central challenge of the present study is under-determinedness for which a set of solutions are examined. Finally, the performance of the proposed method is evaluated by performing a cross-validation on the set of drugs for a specific cell-line.
Keywords:
Dynamical system, State-space model, Network inference, Gene regulatory network, Drug mode-of-action, Under-determinedness, Cancer cell-line
Status : Paper Accepted (Oral Presentation)