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Computation Based Disease Associations in Disease Inference
, J Aghav V
Published in
Pages: 1694 - 1704
With advances in sequencing technologies, large amounts of biological data is easily accessible for research. Advanced techniques to extract biologically relevant knowledge from this data have gained importance. In this paper, we discuss the computation based disease associations that infer human diseases. The biological knowledge of diseases dictates associations between diseases and biological molecules like genes, miRNAs and proteins as well as the associations between diseases and pathways and phenotypes. It is essential to model and represent this knowledge in a computational form with minimal loss of biological context. Based on biological assumptions and statistical analysis, samples of (disease) affected and normal individuals are compared to generate a hypothesis about the disease as depicted by disease associations. We survey computation based disease associations supported by internal interactions i.e interactions between various biological molecules as well as external interactions i.e interactions between the biological molecules and external factors like environment and drugs.
About the journal
JournalProceedings Iwbbio 2014: International Work-Conference on Bioinformatics and Biomedical Engineering, Vols 1 and 2