Executive Summary : | In this project PIs will be develop the artificial intelligent device by using soft computing and deep learning techniques for predicting of breast cancer recurrence and drug response with RNA-seq based platform. The work will help to develop the different prediction approaches that can be apply to distinguish different recurrence of breast cancer at the molecular level using probabilistic and deep machine learning approach with RNA-seq. The work will further allow utilizing its sub-methods for dimension reduction of various RNA-seq high dimensional data that involve different types of cancers. It can be used for following potential applications: 1. Development of breast cancer recurrence and drug response computational device that Predict breast cancer recurrence in early stage by the use of RNA-Seq. 2. Project proposes a novel, automated, efficient and more accurate device for prediction of breast cancer recurrence and drug response based on probabilistic, nature inspired soft computing gene selection technique and deep learning algorithm. 3. The project studies will provide a novel dimension to the treatment and care of breast cancer patients. 4. Further, developed computational model can also be use to predict different types of cancer from high dimensional RNA-seq gene expression data in the field of Bioinformatics. 5. This project will develop various dimension reduction approaches, which can handle big data of other biological domains for finding the optimal features. 6. The developed probabilistic algorithm for gene selection can be use to improve the performance of different machine learning algorithms for different types of Cancer classification and prediction. |
Co-PI: | Dr. Praveen Lalwani, Vellore Institute Of Technology (VIT) Bhopal University, Madhya Pradesh-466114, Dr. Ganesh Narayanan, Jawaharlal Nehru Cancer Hospital And Research Centre, Bhopal, Madhya Pradesh-462001 |