The decision tree is one of the most fundamental ing abstractions. A commonly used type of decision tree is the alphabetic binary tree, which uses (without loss of generality) &quo...
Background: Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be ...
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
Tensors are nowadays a common source of geometric information. In this paper, we propose to endow the tensor space with an affine-invariant Riemannian metric. We demonstrate that ...
We demonstrate and reflect upon the use of enhanced treemaps that incorporate spatial and temporal ordering for exploring a large multivariate spatio-temporal data set. The result...