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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/20843

Title: Early detection of cancer by regression analysis and computer simulation of gene regulatory rules
Authors: Danh, Cong Nguyen
Azadivar, Farhad
???metadata.dc.contributor.url???: congdanh_71@yahoo.com
Keywords: Cancer;Computer simulation;Genetic regulatory network;Microarray data;Probabilistic Boolean Networks (PBN)
Issue Date: 27-Feb-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 144-148
Series/Report no.: Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012)
Abstract: Cellular signaling and dynamic interaction among genes result in stable phenotype structures such as tumor or non tumor cells. Tumor and non-tumor cellular cells often contain some identical cancer causing genes but due to differences in their regulatory networks they evolve differently. As a result, if such regulatory networks are discovered one could predict whether a cell containing particular cancer genes will in fact end up to become a cancerous cell. This paper utilizes a mathematical approach to determine such regulatory rules for a set of cells containing cancer causing genes and uses computer simulation to predict whether in a long run a particular cell will evolve into a cancerous cell. The proposed process utilizes Probabilistic Boolean Networks (PBN) on two gene regulatory networks; one for tumor and one for non-tumor producing structures. The process uses a regression analysis to identify the regulatory networks and a computer simulation model to predict long term cancer potential.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ezproxy.unimap.edu.my:2080/stamp/stamp.jsp?tp=&arnumber=6178972
ISBN: 978-145771989-9
Appears in Collections:Conference Papers

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