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 ...

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

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

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

Graph technology is allowing pharma to model data in a way that offers invaluable insights for marketing, R&D and compliance teams alike.

The company has integrated the AI model into its internal discovery pipeline and aims to use it in collaborative drug discovery programs.

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 ...

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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 ...