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Now that we had a way to handle molecular graphs it was time to implement some parsing capabilities for text-based user input.
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Instead of directly accumulating a molecular graph, it delegates data accumulation to an implementation of SmilesBuilder[A], which must be in implicit scope when creating a new SmilesParser.
A mapping of the atoms of two molecular graphs is called optimal if it maximizes the sum of pairwise atom similarities.
In the deterministic mode, it builds all possible connected molecular graphs that can be represented as subgraphs of MFTA supergraph and satisfy the required constraints.
Although this function is not a valid kernel function [44], it can be used as a similarity function based on molecular graphs.
The enumeration of chemical graphs (molecular graphs) satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics because it leads to a variety of useful applications including structure determination and development of novel chemical compounds.
Obviously, molecular graphs are undirected.
Molecules are represented by molecular graphs.
Molecular graphs are assumed to be simple, undirected graphs.
We used a simple unlabeled connectivity list as the basis for our molecular graphs.
Similarly, convolutional networks were recently applied to molecular graphs, outperforming extended connectivity fingerprints (ECFP) [37].
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