IMPRes: Integrative MultiOmics pathway resolution algorithm and tool | IEEE Conference Publication | IEEE Xplore

IMPRes: Integrative MultiOmics pathway resolution algorithm and tool


Abstract:

A central goal of systems biology is to uncover the underlying functional architecture of the cell and study its mechanisms. To this end, large amounts of omics data are ...Show More

Abstract:

A central goal of systems biology is to uncover the underlying functional architecture of the cell and study its mechanisms. To this end, large amounts of omics data are being rapidly generated, and a focus of bioinformatics research has been towards integrating these data to identify active pathways or modules under certain conditions. Many bioinformatics algorithms include optimization methods, statistical methods, and methods using interaction network topology attributes have been applied for this. Although biologically significant modules can often be detected globally by these methods, it is hard to interpret or make use of the results towards in silico hypothesis generation and testing. We propose a step-wise active pathway detection method (IMPRes) using a dynamic programming approach. First, we take advantage of the existing pathway interaction knowledge in KEGG to build a background network, and then starting from one or multiple receptors of a certain perturbation, we use transcriptomics data collected under these conditions to detect paths that best explain the variations of genes downstream. More other omics data will be integrated in the future. Since dynamic programming enables the detection one step a time, it is easy for biomedical researchers to trace the pathway and finally lead to more accurate drug design and more effective treatment strategies. Additionally, by adding protein-protein interactions in our method, the hypotheses that we generate do not merely utilize existing knowledge, but have potential to discover new knowledge. We have evaluated our method on a dataset of cell wall stress in yeast. The path we found highly agrees with the Cell Wall Integrity (CWI) pathway, which is the main signaling pathway involved in the regulation of cell wall stress responses. We have also compared with other methods on a yeast high osmolality stress dataset and achieved an overall better performance than some other methods. More experiments have been done...
Date of Conference: 13-16 November 2017
Date Added to IEEE Xplore: 18 December 2017
ISBN Information:
Conference Location: Kansas City, MO, USA