{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T05:49:28Z","timestamp":1716270568561},"reference-count":19,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2015,6]]},"abstract":"<jats:p> 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. <\/jats:p>","DOI":"10.1142\/s0219720015410024","type":"journal-article","created":{"date-parts":[[2015,1,12]],"date-time":"2015-01-12T03:12:25Z","timestamp":1421032345000},"page":"1541002","source":"Crossref","is-referenced-by-count":22,"title":["Predicting essential genes and synthetic lethality via influence propagation in signaling pathways of cancer cell fates"],"prefix":"10.1142","volume":"13","author":[{"given":"Fan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Min","family":"Wu","sequence":"additional","affiliation":[{"name":"Data Analytic Department, Institute for Infocomm Research, A*STAR, Singapore 138632, Singapore"}]},{"given":"Xue-Juan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Xiao-Li","family":"Li","sequence":"additional","affiliation":[{"name":"Data Analytic Department, Institute for Infocomm Research, A*STAR, Singapore 138632, Singapore"}]},{"given":"Chee Keong","family":"Kwoh","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Jie","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"Genome Institute of Singapore, A*STAR, Singapore 138672, Singapore"}]}],"member":"219","published-online":{"date-parts":[[2015,5,15]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1186\/gm99"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1038\/nrc1691"},{"key":"rf3","first-page":"71","volume":"13","author":"Wu M.","year":"2014","journal-title":"Cancer Informatics"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003637"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1055"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1038\/nrm2041"},{"key":"rf8","first-page":"169034","volume":"2014","author":"Li X. 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