4 papers
Predicting Protein-Nucleic Acid Flexibility Using Persistent Sheaf Laplacians
Nicole Hayes, Ekaterina Merkurjev, Guo-Wei Wei
Understanding the flexibility of protein-nucleic acid complexes, often characterized by atomic B-factors, is essential for elucidating their structure, dynamics, and functions, suc…
A General Framework for Group Sparsity in Hyperspectral Unmixing Using Endmember Bundles
Gokul Bhusal, Yifei Lou, Cristina Garcia-Cardona +1
Due to low spatial resolution, hyperspectral data often consists of mixtures of contributions from multiple materials. This limitation motivates the task of hyperspectral unmixing…
MALADY: Multiclass Active Learning with Auction Dynamics on Graphs
Gokul Bhusal, Kevin Miller, Ekaterina Merkurjev
Active learning enhances the performance of machine learning methods, particularly in semi-supervised cases, by judiciously selecting a limited number of unlabeled data points for…
Persistent Sheaf Laplacian Analysis of Protein Flexibility
Nicole Hayes, Xiaoqi Wei, Hongsong Feng +2
Protein flexibility, measured by the B-factor or Debye-Waller factor, is essential for protein functions such as structural support, enzyme activity, cellular communication, and mo…