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In order to provide some human-readable output for our molecular graphs, we implemented type class Show for trait LGraph.
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Since the specification we have so far described can be used to reconstitute the molecular graph, we can now venture to study the most optimal approaches to enabling some of the most common tasks in cheminformatics.
Since we are dealing with molecular graphs of relatively simple structural complexity, the use of dedicated graph isomorphism algorithms, e.g. for planar graph [ 48], could increase the performance as well.
Now that we had a way to handle molecular graphs it was time to implement some parsing capabilities for text-based user input.
In order to perform this analysis in metabolic networks, we used the molecular signature descriptor, a 2D representation of molecular graphs that provides a characterization of compounds and reactions in the network.
We used a simple unlabeled connectivity list as the basis for our molecular graphs.
We hypothesize that principles behind polypharmacology are embedded in paired fragments in molecular graphs and amino acid sequences of drug-target interactions.
We show them graphs: we have a lot of figures.
Obviously, molecular graphs are undirected.
Molecular graphs are assumed to be simple, undirected graphs.
We optimized the VF2 algorithm with the strategies presented in Shang publication [28] and used by Zhu for the search of molecular graphs into molecular databases [29].
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