What is it about?
This work is about using mathematical techniques for the prediction of cancer at a very early stage so that it can be reversed. Measures of Information Theory have been applied to study a particular type of cancer (KIRC) and the results have been elucidated.
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Why is it important?
Cancer is a disease that is easier to handle if predicted early. If it is predicted early enough at the epigenetic stage, it can be reversed. Our work has techniques that aim to analyze DNA methylation data (epigenetic data) for cancer in order to predict it early and reverse it.
Perspectives
The techniques used in our work can be applied to different diseases that are caused to aberrant DNA methylation, not just cancer . We believe that this work lays a foundation in the area of Computational Epigenetics , particularly applied to disease prediction.
Nithya Ramakrishnan
Indian Institute of Technology Delhi
Read the Original
This page is a summary of: Analysis of healthy and tumour DNA methylation distributions in kidney-renal-clear-cell-carcinoma using Kullback-Leibler and Jensen-Shannon distance measures , IET Systems Biology, March 2017, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-syb.2016.0052.
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