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Báo cáo y học: " Indirect genomic effects on survival from gene expression data"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: Indirect genomic effects on survival from gene expression data. | Open Access Method Indirect genomic effects on survival from gene expression data Egil Ferkingstad Arnoldo Frigessi and Heidi Lyng Addresses Department of Biostatistics and sfi 2 Statistics for Innovation University of Oslo Gaustadalleen Oslo NO-0314 Norway. Centre for Integrative Genetics Norwegian University of Life Sciences Arboretveien Aas NO-1432 Norway. Department of Radiation Biology Institute for Cancer Research Norwegian Radium Hospital Montebello Oslo NO-0310 Norway. Correspondence Egil Ferkingstad. Email egil.ferkingstad@medisin.uio.no Published 22 March 2008 Genome Biology 2008 9 R58 doi 10.1 186 gb-2008-9-3-r58 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2008 9 3 R58 Received 14 November 2007 Revised 24 January 2008 Accepted 22 March 2008 2008 Ferkingstad et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract In cancer genes may have indirect effects on patient survival mediated through interactions with other genes. Methods to study the indirect effects that contribute significantly to survival are not available. We propose a novel methodology to detect and quantify indirect effects from gene expression data. We discover indirect effects through several target genes of transcription factors in cancer microarray data pointing to genetic interactions that play a significant role in tumor progression. Background There exists a large literature studying associations between survival and high throughput gene expression data 1-5 . Also much work has been done to elaborate pathways and regulatory networks 6-10 . We have developed a new method combining survival and pathway analysis technologies aiming at a causal understanding of how gene .