In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clu...
Tobias Wittkop, Jan Baumbach, Francisco P. Lobo, S...
Detecting objects in complex scenes while recovering the scene layout is a critical functionality in many vision-based applications. Inspired by the work of [18], we advocate the ...
This paper proposes an organized generalization of Newman and Girvan’s modularity measure for graph clustering. Optimized via a deterministic annealing scheme, this measure prod...
In this paper, we present an algorithm to lay out a particular class of graphs coming from real case studies: the quasi-tree graph class. Protein and internet mappings projects ha...