Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
We have shown how to construct multiresolution structures for reversing subdivision rules using global least squares models 16. As a result, semiorthogonal wavelet systems have al...
Faramarz F. Samavati, N. Mahdavi-Amiri, Richard M....
In this paper, we present a new visibility-based feature extraction algorithm from discrete models as dense point clouds resulting from laser scans. Based on the observation that ...
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
Abstract. We present a framework for modelling heterogeneous distributed systems using graph transformations in the Synchronized Hyperedge Replacement approach, which describes com...