Models
Emerging health geography research analyzes and visualizes health behaviors and outcomes in relation to urban environmental data and related official statistics to produce “health reports” for specific areas. This can be extended to developments in urban planning, e.g., to identify districts or neighborhoods for social investments or restrictions.
We mapped anthropometric data the large LIFE Adult population (10,000 participants) onto the Leipzig map. In particular, we derived the body mass index ...
Creator: Ying-Chi Lin
Submitter: René Hänsel
Model type: Not specified
Model format: Not specified
Environment: Not specified
Analysis of large-scale molecular biological data using self-organizing maps
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 ...
Creator: Henry Löffler-Wirth
Submitter: Henry Löffler-Wirth
Model type: Not specified
Model format: R package
Environment: Shiny
oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization. These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular ...
Creator: Henry Löffler-Wirth
Submitter: René Hänsel
Model type: Self-Organizing Map
Model format: R package
Environment: Shiny