In biology textbooks and beyond, the human genome and DNA therein typically are taught in only one dimension. While it can be ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Caltech scientists have found a fast and efficient way to add up large numbers of Feynman diagrams, the simple drawings ...

Here, molecular graphs derived from the one-electron density matrix are introduced within a more general effort to explore whether incorporating electronic structure awareness allows a single model to ...

Patterns of receptor−ligand interaction can be conserved in functionally equivalent proteins even in the absence of sequence homology. Therefore, structural comparison of ligand-binding pockets and ...

Understanding the underlying graph structure of a nonlinear map over a particular domain is essential in evaluating its potential for real applications. In this paper, we investigate the structure of ...

Heterogeneous dynamics, strongly nonlinear and nonaffine structures, and cooperation–antagonism networks are considered together in this work, which have been considered as challenging problems in the ...