Data is becoming increasingly prevalent in every field, and bioinformatics is ripe for innovation in data acquisition with no insights being derived from experiments daily, a streamline way to query and use this data for analysis will be very important in the future of personalized cancer research.
What it does
The web application contains form fields where the user simply selects the disease for which they want all available gene expression values available at the National Cancer Institute Genomic Data Commons. Upon requesting, the data, an API call is made to acquire the data, the data is parsed into a table, and displayed.
How we built it
The API queries were performed in python, and the web integration was built on the Django framework.
Challenges we ran into
Neither of us had experience using the bulk of these technologies, so we were continually learning as we went on. A particular challenge was figuring out how to use Django to do form requests.
Accomplishments that we're proud of
Creating a UI that makes it seamless to acquire particular data from NCI and Pubmed
What we learned
The basics of the Django framework, and how to use data portal APIs
What's next for UTH
Now that our webapp can receive the data, we would like to offer online services to auto analyze with open source software in both python and R.