Engineer uses advanced deep learning to predict where proteins will localize within cells

A Mizzou Engineer is developing computational tools that can be used to predict where proteins will localize within a cell. Using highly advanced deep learning, the resource could help researchers better understand how proteins function or, if positioned incorrectly within a cell, misfire and cause problems.

Engineer proposes deep learning system to speed drug development

A Mizzou Engineer has proposed a new deep learning system that would speed up drug development by more accurately predicting how drugs and proteins interact.

New protein prediction tool could accelerate biological discoveries

A Mizzou Engineering team has released new software that will allow computers to automatically predict protein interactions.

Meet Jianlin “Jack” Cheng

Solving problems one protein at a time

Protein Prediction Challenge Makes History – and Mizzou Engineers Rank in Top 10

Mizzou Engineering students took on tech giants at a worldwide competition last month and came home in the top 10 for devising a way to accurately predict protein structures. And in subcategories, Mizzou teams ranked in the top 3.

Cheng Receives $1.37M NIH Grant to Predict Protein Structures

Knowing the three-dimensional structure of proteins—such as the shape of the spike-like protein that injects coronavirus into our cells—can help us treat illnesses. That’s one reason why predicting protein structures remains one of the world’s highest health priorities. Mizzou Engineering Jianlin Cheng has been working on protein prediction methods for more than a decade.