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Personalized Medicine: Redefining Cancer Treatment

In this project, we are going to predict the effect of Genetic Variants to enable Personalized Medicine.
4.74.7

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What will you learn

  • Working on Text Data of Genetics
  • Creating genetic Worcloud
  • Advanced preprocessing on Text mining
  • Building Classification models like knn-methods, logistic regression
  • Working with Keras

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Python 3.6 with Anaconda
  • This project assumes that you have a good knowledge of Data Science and the Python language. If not - we recommend you to take the Data Science in Python course first.

Project Description

A lot has been said during the past several years about how precision medicine and, more concretely, how genetic testing is going to disrupt the way diseases like cancer are treated.

But this is only partially happening due to the huge amount of manual work still required. In this project, we will try to take personalized medicine to its full potential.

Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). 

Currently, this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from the text-based clinical literature.

For this project, MSKCC is making available an expert-annotated knowledge base where world-class researchers and oncologists have manually annotated thousands of mutations.

MSKCC(Memorial Sloan Kettering Cancer Center) is making available an expert-annotated knowledge base where world-class researchers and oncologists have manually annotated thousands of mutations.

In this project, we are going to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classified genetic variations.

Instructors

 
Shaik

Data Scientist / Business Consultant at GE

3 years of rich working experience in BIG Data, Business Intelligence & Analytics with CMMI Level 5 Organizations in BFSI, Manufacturing Sector. Excellent written and oral communications, strong analytical and problem solving capabilities. Constantly learning and experimenting emerging open source tools and technologie see more...