Collective behavior involving distally separate regions in a protein is known to widely affect its function. In this paper, we present an online approach to study and characterize ...
Arvind Ramanathan, Pratul K. Agarwal, Maria Kurnik...
This paper explores the use of multi-dimensional trees to provide spatial and temporal e ciencies in imaging large data sets. Each node of the tree contains a model of the data in...
Background: Phenomenological information about regulatory interactions is frequently available and can be readily converted to Boolean models. Fully quantitative models, on the ot...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...