Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Background: Protein structure comparison is a fundamental task in structural biology. While the number of known protein structures has grown rapidly over the last decade, searchin...
Lei Zhang, James Bailey, Arun Siddharth Konagurthu...
This paper reports some experiments in using SVG (Scalable Vector Graphics), rather than the browser default of (X)HTML/CSS, as a potential Web-based rendering technology, in an a...
The techniques described in this paper allow multiscale photon-limited image reconstruction methods to be implemented with significantly less computational complexity than previou...
Background: Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often use...
Matthew Hansen, Logan Everett, Larry Singh, Sridha...