In:
Journal of Bioinformatics and Computational Biology, World Scientific Pub Co Pte Ltd, Vol. 13, No. 03 ( 2015-06), p. 1541002-
Abstract:
A major goal of personalized anti-cancer therapy is to increase the drug effects while reducing the side effects as much as possible. A novel therapeutic strategy called synthetic lethality (SL) provides a great opportunity to achieve this goal. SL arises if mutations of both genes lead to cell death while mutation of either single gene does not. Hence, the SL partner of a gene mutated only in cancer cells could be a promising drug target, and the identification of SL pairs of genes is of great significance in pharmaceutical industry. In this paper, we propose a hybridized method to predict SL pairs of genes. We combine a data-driven model with knowledge of signalling pathways to simulate the influence of single gene knock-down and double genes knock-down to cell death. A pair of genes is considered as an SL candidate when double knock-down increases the probability of cell death significantly, but single knock-down does not. The single gene knock-down is confirmed according to the human essential genes database. Our validation against literatures shows that the predicted SL candidates agree well with wet-lab experiments. A few novel reliable SL candidates are also predicted by our model.
Type of Medium:
Online Resource
ISSN:
0219-7200
,
1757-6334
Language:
English
Publisher:
World Scientific Pub Co Pte Ltd
Publication Date:
2015
SSG:
12
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