IT Services for Decision Support Systems on Public Health Problems by using Genomic Data

Cuevas-Tello, J.C., Garcia-Sepulveda, C.A., Pérez-González, H.G., Mora, M.
International Conference on Bioinformatics & Computational Biology (BIOCOMP-2010), Las Vegas, Nevada, USA. (2)801-806 , 2010.


We present a framework for the servitization of a Decision Support System (DSS). As we want to provide this DSS as a service, we base our framework on the IT Services technology. We focus our DSS on public health problems, and we use genomic data to guide our DSS. The natural killer cells (NK), in particular immunoglobulinÄìlike receptor (KIR) genes, are part of our auto-immunity system. Therefore the presence or absence of these genes can be associated with diseases including viral infections (influenza) and cancer. Several studies have been done reporting disease associations with HLA-KIR gene combinations including a couple of genes. This research focus on studying the complete set of KIR genes. We attempt to predict, via a DSS, whether or not somebody can be protected through their KIR genes against diseases such as influenza and cancer. We present a framework for servitizing a DSS based on support vector machines (SVMs), where SVMs are the state-of-the-art on classification methods in machine learning. Results using artificial data are presented, showing that this is a promising approach.