Bio-Prodict Internships

Research Minor

In 2015 I started a Research Minor at Bio-Prodict. This project involved an intermediate level data science project concerning the development of a pathogenicity predictor, trained and verified on a dataset concerning a specific genetic disorder.

Technologies used

• Python, with scikit-learn and pandas for data science.
• Git and Jenkins for source control and continuous integration.
• Working with and administrating Linux Systems.

Graduation internship

After my research minor Bio-Prodict asked me to continue my data science work as part of my graduation internship in 2016. We decided to start work on more advanced, neural network-based solutions to learning about protein properties.

Technologies used

• Convolutional and Dense neural networks with Keras for protein analysis.
• Recurrent Neural Networks with Keras for literature analysis.
• Integrating solution optimization efforts with monitoring dashboards like Tensorboard and FGLab.

The video above was produced with PyMol and and the GreenSock Animation Platform for HTML/CSS/JS animations.

Molviewer Plugin

During both periods I was in charge of rewriting the code for the 3DM plugin for YASARA and PyMol. This plugin provides integration for these molecular viewers with Bio-Prodict's 3DM platform.

Technologies used

• YASARA and PyMol plugin platforms.
• Advanced level, high quality Python code, developed according to PEP8 and PyLint standards.
• Jenkins for code quality monitoring and deployment pipelines.