Inference of tumor inhibition pathways from drug perturbation data

Saad Haider, Ranadip Pal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The tumor proliferation pathways for each individual patient encompass variations and a successful treatment regime based on targeted drugs necessitates the estimation of the influences of target inhibition on cell viability. In this article, we consider an inference approach to decipher the significant blocks of protein targets and the effect of their inhibition on tumor proliferation. Our framework is based on sequential search and non-linear optimization for estimating the block parameters. The proposed algorithm is tested on extensive synthetic data and provides high accuracy estimates for model parameters. We furthermore evaluated the performance of the framework in presence of noise and were able to achieve high precision cell viability prediction.

Original languageEnglish
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages95-98
Number of pages4
DOIs
StatePublished - 2013
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Conference

Conference2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

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