Protein-protein interaction plays an important role in studying the mechanism of protein
functions from the structural perspective. Molecular docking is a powerful approach to detect …

Klebsiella pneumonia is a Gram negative facultative anaerobic bacterium involved in
various community-acquired pneumonia, nosocomial and lungs associated infections …

Despite their satisfactory performance, most existing listwise Learning-To-Rank (LTR)
models do not consider the crucial issue of robustness. A data set can be contaminated in …

Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of
the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and …

Background Predictive models utilizing social determinants of health (SDH), demographic
data, and local weather data were trained to predict missed imaging appointments (MIA) …

Personalized drug response prediction is an approach for tailoring effective therapeutic
strategies for patients based on their tumors' genomic characterization. While machine …

Despite their empirical success, most existing listwiselearning-to-rank (LTR) models are not
built to be robust to errors in labeling or annotation, distributional data shift, or adversarial …

The prediction of the proteolytic susceptibility of the metalloenzyme-target protein complexes
has been a little-explored field of protein-protein interactions (PPI). Thus, the development …

This dissertation develops a comprehensive statistical learning framework that is robust to
(distributional) perturbations in the data using Distributionally Robust Optimization (DRO) …

Proteins are large macromolecules that play critical roles in many cellular activities in living
organisms. These include catalyzing metabolic reactions, mediating signal transduction …