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+# Deep Learning for Cancer Therapy [![Build Status](https://travis-ci.org/skjena/cnnCancerTherapy.svg?branch=master)](https://travis-ci.org/skjena/cnnCancerTherapy)
+
+[![Grayscale Preview](https://github.com/skjena/cancerTherapy/blob/testing/docs/Poster.jpg?raw=true)](https://blackrockdigital.github.io/startbootstrap-grayscale/)
+
+## Motivation:  
+Machine learning can be used to perform unsupervised learning on the DNA sequences of patient tumors in order to  identify non-linear features of the tumor DNA that help predict treatment.  
+
+## Goal:  
+To use deep learning to identify patients whose tumor DNA mutations “look similar to” other tumors for which treatments are effective.  
+
+## Platforms: 
+TensorFlow
+
+## Installations:
+Installing Tensorflow: https://www.tensorflow.org/versions/r1.8/install/
+
+## Team & Contact:  
+|Suraj Jena                <skjena@ucdavis.edu>|  
+|Kumud Ravisankaran <kravisankaran@ucdavis.edu>|  
+|Valeria Brewer        <valramirez@ucdavis.edu>|  
+|Ninad Mehta              <ntmehta@ucdavis.edu>|  
+
+#### Project no longer maintained, due to absence of cloud credits since this was a research project & proof-of-concept was complete. Contact @author if interested in a HOWTO, or getting it back up.