%0 Journal Article %1 Fang:2014:Genome-Med:25246945 %A Fang, H %A Gough, J %D 2014 %J Genome Med %K DNET MUSTREAD TCGA cancer-research fulltext software %N 8 %P 64-64 %R 10.1186/s13073-014-0064-8 %T The 'dnet' approach promotes emerging research on cancer patient survival %U https://www.ncbi.nlm.nih.gov/pubmed/25246945 %V 6 %X We present the 'dnet' package and apply it to the 'TCGA' mutation and clinical data of >3,000 patients. We uncover the existence of an underlying gene network that at least partially controls cancer 'survivalness', with mutations that are significantly correlated with patient survival, yet independent of tumour origin and type. The survivalness network has natural community structure corresponding to tumour hallmarks, and contains genes that are potentially druggable in the clinic. This network has evolutionary roots in Deuterostomia identifying PTK2 and VAV1 as under-valued relative to more studied genes from that era. The 'dnet' R package is available at http://cran.r-project.org/package=dnet.

@article{Fang:2014:Genome-Med:25246945, abstract = {We present the 'dnet' package and apply it to the 'TCGA' mutation and clinical data of >3,000 patients. We uncover the existence of an underlying gene network that at least partially controls cancer 'survivalness', with mutations that are significantly correlated with patient survival, yet independent of tumour origin and type. The survivalness network has natural community structure corresponding to tumour hallmarks, and contains genes that are potentially druggable in the clinic. This network has evolutionary roots in Deuterostomia identifying PTK2 and VAV1 as under-valued relative to more studied genes from that era. The 'dnet' R package is available at http://cran.r-project.org/package=dnet.}, added-at = {2017-04-29T01:08:08.000+0200}, author = {Fang, H and Gough, J}, biburl = {https://www.bibsonomy.org/bibtex/28e2888a93554b752bf8ed1dab8c76504/marcsaric}, description = {The 'dnet' approach promotes emerging research on cancer patient survival. - PubMed - NCBI}, doi = {10.1186/s13073-014-0064-8}, interhash = {f2d751681c736ef6ed3a6c77b960652d}, intrahash = {8e2888a93554b752bf8ed1dab8c76504}, journal = {Genome Med}, keywords = {DNET MUSTREAD TCGA cancer-research fulltext software}, number = 8, pages = {64-64}, pmid = {25246945}, timestamp = {2017-10-07T23:53:06.000+0200}, title = {The 'dnet' approach promotes emerging research on cancer patient survival}, url = {https://www.ncbi.nlm.nih.gov/pubmed/25246945}, volume = 6, year = 2014 }