Beschreibung
In todays world of biology and medicine, DNA has become an extremely useful tool for predicting a disease. Most diseases are not triggered by a single gene but by a combination of genes together. Most disease phenotypes are genetically complex, with contributions from combinations of genetic variation in different loci. A fundamental problem in human health is to predict the effect of genes that cause disease; this is an important step to diagnosis and treatment. In this project, we propose an approach to predict the diseases occurring due to mutations even before it has surfaced and detected in other tests. Our proposed system takes into consideration only those genes which can have an impact on the cause of the diseases to a fairly large extent and hence remove negligible data. Consideration of prominent genes is done by applying Bayesian Network, specifically using concepts of pathway analysis which provides a pathway of the causal gene and the supporting (associated) genes.
Autorenporträt
Sushma M. Suresha is a graduate from Vishvesvaraya Technological University, Karnataka, India. Currently working as a software engineer at Robert Bosch Engineering and Business Solutions private limited, Bengaluru. A budding engineer who is keenly working on DNA analysis, has recently published a paper on DNA based Disease Prediction in IEEE.
