Gene expression and DNA methylation profiling allows clinical diagnosis to be made on a molecular level, thereby substantially increasing diagnosis accuracy and facilitating choice of treatment based on the patients’ genetic traits. Moreover, identifying disease-related genes and monitoring their activity levels provide insights into disease mechanisms. We aim improve methods for disease diagnosis and marker selection by integrating additional sources of data and the design of methods capable of handling high dimensional spaces.
Pablo Andreta Jakoswiak (former member)
Marcelo Ferreira (former member)
Sonja Hanzelmann (former member)
Axelsson A.S., Mahdi T. , Nenonen H.A. , Singh T., Hänzelmann S. , … , Costa I.G., Zhang E., Rosengren A.H., Sox5 regulates beta-cell phenotype and is reduced in type 2 diabetes, Nature Communications, in print.
de Almeida, D., Ferreira, M. R. P., Franzen, J., Weidner, C., Frobel, J., Zenke, M. Costa, I.G., Wagner, W. (2016). Epigenetic Classification of Human Mesenchymal Stromal Cells. Stem Cell Reports, 6(2):68-175 [paper].
Hanzelmann S, Wang J, Guney E, Tang Y, Zhang E, Axelsson AS, Nenonen H, Salehi AS, Wollheim CB, Zetterberg E, Berntorp E., Costa IG, Castelo R, Rosengren AH, Thrombin stimulates insulin secretion via protease-activated receptor-3, Islets, 7(4):e1118195.
Jaskowiak, PA , Campello, RJGB, Costa, IG., On The Selection of Appropriate Distances for Gene Expression Data Clustering, BMC Bioinformatics, 15(Suppl 2):S2[paper].
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