Even though CNNs achieve great success in performing complex intelligence tasks, this achievement comes with an overwhelming cost. Modern CNN architectures require hundreds of stacked convolution layers, performing billions of operations for a single input.
We will develop machine learning methods to classify protein-protein docking poses as correct or incorrect. We will improve the balance of the training set by employing SMOTE and GANs and the variance and size by the Snorkel technique. Our methods will be applicable to life sciences and bioengineering.
Fisheries play a vital role in global food supply and are becoming key components in countries’ economy.
Problem we are facing: Because of the massive computational burden of typical inverse CFD design process, searching a wide variety of input geometry shape to optimize a payoff function (e.g. drag) is infeasible.
Glycosylation is a post-translational modification widely implicated in structural and functional attributes of the cell. Changes in glycosylation patterns are associated with invasiveness, acquisition of virulence features promoting metastasis, and epithelial-mesenchymal transition in a wide range of solid tumors.