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> -wrap-foot> Finding the best scoring path in a weighted graph is another frequently occurring task.
Integration is achieved by building an overlap graph from pairwise aligned contigs and subsequently finding the highest scoring path.
For example, finding the best scoring path connecting two proteins in the STRING network is a crucial part of the NetworKIN algorithm (Linding et al., 2007).
This makes finding the global optimum computationally expensive; therefore, we search for the highest scoring path using a Tabu procedure (Glover, 1986).
If, for instance, the source set S and target set T both contain one node, the problem reduces to finding the highest scoring path between them.
Assembly integration is finally achieved by finding a highest scoring path between the start and end nodes in the overlap graph and calling the consensus (Fig. 1F).
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The increasing service providers factor scored path coefficient of - 0.14 and the uncertainty about the market factor obtained - 0.08.
The algorithm works as follows: firstly, map links nearby the first trace point are picked and each one will constitute a scored path candidate (a possible match sequence).
For every node in the start list A, the recursive search is computed towards every node in the target list B. A results tab with scored paths is not created in this case.
Selected high scoring paths are shown in Figure 2. Two serine/threonine-protein phosphatases, 2A (PP2andand 5 (PP5) were members of the most upregulated paths in early insulitis (Figure S2).
Finally, the algorithm returns the top scoring paths, along with the chosen label for each node in each path.
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