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Many of the current transcript assembly algorithms attempt to reproduce each of the isoforms available to a gene using a bipartite graph approach, which can lead to reporting of statistically probable, but non-real isoforms and dilution of expression levels of real isoforms as reads are assigned to the non-real isoforms.
Our results were obtained using a bipartite network to model the spread of the disease.
We constructed the drug target interaction network for each protein class using a bipartite graph representation.
We constructed the drug target interaction network for each protein class using a bipartite graph representation (Yildirim et al., 2007).
We used a bipartite spectral graph partitioning algorithm of [ 32].
We use a bipartite graph to represent the RA-CORP problem, and then use a sparse matrix-based algorithm to find the maximum-sized matching between the MNs and RNs.
At first, we use a bipartite graph to represent the relation between formulas and minimal inconsistent subsets of a knowledge base.
Bipartite spectral clustering uses a bipartite graph where vertices are divided into two types, each from one dimension of the given contingency table (T).
We used a bipartite networks to construct the relationships of our data.
The differences between bar codes were calculated using a maximal bipartite graph matching algorithm.
But, soon, matches will be made using a complex algorithm.
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