We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks...
Steve Dworschak, Susanne Grell, Victoria J. Nikifo...
Background: A number of studies on biological networks have been carried out to unravel the topological characteristics that can explain the functional importance of network nodes...
Background: Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Background: Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the inter...
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
Background: Biochemical networks play an essential role in systems biology. Rapidly growing network data and e research activities call for convenient visualization tools to aid i...
Sheng He, Juan Mei, Guiyang Shi, Zhengxiang Wang, ...
Background: The increasing availability and diversity of omics data in the post-genomic era offers new perspectives in most areas of biomedical research. Graph-based biological ne...
Alexander Martin, Maria Elena Ochagavia, Laya C. R...
Motivation: The functioning of biological networks depends in large part on their complex underlying structure. When studying their systemic nature many modeling approaches focus ...
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...