Predicting transporter proteins

In bioinformatics, transporter proteins correspond to a family of proteins that are specialized to transporting various metabolites through cell walls. Understanding transporter proteins is essential in e.g., analyzing the interactive between cells and the environment, modeling the dynamics of biochemical reactions. In this recent project, we aim to reliably predict the transporter classification (TC) of an arbitrary protein with machine learning approaches. The transporter classification is a hierarchical classification scheme where each element in the hierarchy is a category of a function. The preliminary results demonstrate the proposed machine learning framework is very accurate in transporter protein prediction achieving about 99% accuracy and 98% AUC over a collection of 12000 proteins.

For detailed information of our machine learning approaches and preliminary results, please refer to the project webpage in GitHub.

Hongyu Su 25 August 2015