%0 Journal Article %1 LofflerWirth:2015:Bioinformatics:26063839 %A Löffler-Wirth, H %A Kalcher, M %A Binder, H %D 2015 %J Bioinformatics %K bioconductor fulltext mach machine-learning mustread software %N 19 %P 3225-3227 %R 10.1093/bioinformatics/btv342 %T oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor %U https://www.ncbi.nlm.nih.gov/pubmed/26063839 %V 31 %X Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms.oposSOM is now publicly available as Bioconductor R package.wirth@izbi.uni-leipzig.deSupplementary data are available at Bioinformatics online.

@article{LofflerWirth:2015:Bioinformatics:26063839, abstract = {Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms.oposSOM is now publicly available as Bioconductor R package.wirth@izbi.uni-leipzig.deSupplementary data are available at Bioinformatics online.}, added-at = {2020-02-11T23:40:41.000+0100}, author = {L{\"o}ffler-Wirth, H and Kalcher, M and Binder, H}, biburl = {https://www.bibsonomy.org/bibtex/23f556a79a73e864f1cdd1fc13f910295/marcsaric}, description = {oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor. - PubMed - NCBI}, doi = {10.1093/bioinformatics/btv342}, interhash = {0d27a8bd150c376888fc98d502bdcb28}, intrahash = {3f556a79a73e864f1cdd1fc13f910295}, journal = {Bioinformatics}, keywords = {bioconductor fulltext mach machine-learning mustread software}, month = oct, number = 19, pages = {3225-3227}, pmid = {26063839}, timestamp = {2020-02-11T23:41:28.000+0100}, title = {oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor}, url = {https://www.ncbi.nlm.nih.gov/pubmed/26063839}, volume = 31, year = 2015 }