SigSim
Researchers
Carina Kirschner BSc.
Susanne Schaller MMSc.
Dr. Julia Vetter MSc.
Duration
Research Areas
Partners
University of Applied Sciences Upper Austria, Hagenberg Campus, RG Bioinformatics
University of Applied Sciences Upper Austria, Linz Campus, NASAN
University of Salzburg, Department of Biosciences and Medical Biology, AG Horejs-Hoeck
(Université d’Artois)
SigSim (Signaling pathway simulation using white-box modeling for the prediction of gene expression in cells)
Gene expression and the associated expression of proteins are the most important influencing factors in inter- and intracellular signaling pathways. All processes in our cells are controlled by mutual influence, activation, inactivation, inhibition, and other interactions between these variables. A better understanding of these mechanisms offers great potential in the development of innovative therapeutic approaches and a deeper insight into a wide variety of cell mechanisms and diseases.
This project uses machine learning methods, especially white-box modeling algorithms, to investigate the effects of gene expressions in signaling pathways. The aim is to simulate the (in)activation of different genes and the effects on other genes. By simulating signaling pathways by training models using data from healthy individuals, we aim to identify critical nodes within signaling pathways after applying these models to data from afflicted individuals or abnormal data.
The prediction of gene expression and gene expression profiles in combination with the simulation of signaling pathways offers immense possibilities, such as in the development of drugs or deeper insights into a wide variety of cell mechanisms and diseases.
Involved partners: The expertise at the Upper Austria University of Applied Sciences (FH OÖ), Campus Hagenberg and Campus Linz, is supported by collaboration partners from the Université d'Artois and Paris Lodron University of Salzburg.