Wolfram Computation Meets Knowledge

Wolfram Summer School


Madeleine Sutherland

Science and Technology

Class of 2018


Madeleine Sutherland is a chemistry PhD student at the Massachusetts Institute of Technology. She works in the Koehler Lab in the Koch Institute for Integrative Cancer Research, where she studies molecular recognition in the context of optimizing drugs with nontraditional targets/mechanisms. She is interested in using theory and methods from physical organic chemistry to do drug quantitative structure-activity relationship studies more efficiently and rationally; she hopes particularly to explore the relationship between electronic/quantum chemical structure and biological activity. On the programming side, she is working on automating the process of building models from chemical/computational data in a flexible way, and sees potential applications for machine learning algorithms down the road.

Computational Essay: Visualizing Multivariable Functions in Chemistry Using Mathematica

Project: Interpreting Drug Quantitative Structure-Activity Relationship (QSAR) Data in Mathematica

Project Overview

Wolfram Language facilitates data analysis and 3D structure image generation. However, for this data set, machine learning models provide no advantage over Multiple Non-Linear Regression.