Background: The number of algorithms available to predict ligand-protein interactions is large and ever-increasing. The number of test cases used to validate these methods is usua...
Luis A. Diago, Persy Morell, Longendri Aguilera, E...
This paper presents a new approach to discriminative modeling for classi cation and labeling. Our method, called Boosting on Multilevel Aggregates (BMA), adds a new class of hiera...
Proteins are highly flexible and large amplitude deformations of their structure, also called slow dynamics, are often decisive to their function. We present a two-level rendering ...
Ove Daae Lampe, Ivan Viola, Nathalie Reuter, He...
In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of "sharpness" and the joint registration-segmentation o...
B. T. Thomas Yeo, Mert R. Sabuncu, Rahul Desikan, ...
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...