Sentence examples for bipartite framework from inspiring English sources
This complexity is brought about through the widespread presence of antagonism between Pseudonocardia bacteria maintained by different ant colonies, species, and genera, but also by the presence of additional symbiont lineages (the Escovopsis parasites) that likely adjust the dynamics of cooperation and conflict within associations previously examined in a bipartite framework.
Social pacts, bipartite or tripartite framework agreements on wage setting 37.
MF and MK designed the bipartite Boolean modelling framework.
To robustly solve the problem of tracking centrosomes in developing C.elegans embryos, we have extended a bipartite matching based framework for object tracking (Kalaidzidis, 2007) to incorporate prior knowledge of the centrosome cycle (see the following subsection).
More precisely, Murray et al. used latent semantic analysis and neural networks [26] and Hu et al. used a Bayesian framework and a bipartite pages-users network [27] to predict a user's gender from their browsing history.
In this work we introduce another context in which bipartite networks provide the natural framework to study epidemic spreading, namely those vector-borne diseases in which transmission occurs exclusively between vectors and hosts.
The predominant framework is a bipartite graph where nodes representing molecules are connected to nodes representing interactions.
The other statistical approach is the distance learning in the framework of supervised bipartite graph inference (Yamanishi, 2009; Yamanishi et al., 2008).
Similarly, the integration of the chemical, bimolecular, and clinical information was made to design a general framework based on bipartite network projections, and the drug ranking was calculated by kernelized score functions [ 12].
The proposed method consists of two steps: (i) prediction of pharmacological effects from chemical structures of given compounds and (ii) inference of unknown drug target interactions based on the pharmacological effect similarity in the framework of supervised bipartite graph inference.
The originality of the proposed method lies in prediction of pharmacological effects from chemical structures of given compounds, and its use for identification of unknown drug target interactions in the framework of supervised bipartite graph inference.
