[en] Genes, proteins, or cells influence each other and consequently create patterns, which can be increasingly better observed by experimental biology and medicine. Thereby, descriptive methods of statistics and bioinformatics sharpen and structure our perception. However, additionally considering the interconnectivity between biological elements promises a deeper and more coherent understanding of melanoma. For instance, integrative network-based tools and well-grounded inductive in silico research reveal disease mechanisms, stratify patients, and support treatment individualization. This review gives an overview of different modeling techniques beyond statistics, shows how different strategies align with the respective medical biology, and identifies possible areas of new computational melanoma research.
H2020 ; 642295 - MEL-PLEX - Exploiting MELanoma disease comPLEXity to address European research training needs in translational cancer systems biology and cancer systems medicine
FnR ; FNR7643621 > Thomas Sauter > Melanoma sensitivity > Predicting individual sensitivity of malignant melanoma to combination therapies by statistical and network modeling on innovative 3D organotypic screening models > 01/05/2015 > 30/04/2018 > 2013
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