We map the synthetic chemistry domain into a graph-like data model to leverage algorithms initially developed and optimized in other fields, like social networks and sentiment analysis. Instead of adapting these algorithms to our particular scientific area's needs (and language), LinChemIn contains flexible machinery to morph the SynGraph model to suit the technical requirements of specific graph libraries. This approach allows the LinChemIn user and developer to focus on the chemistry domain rather than modifying or reimplementing graph algorithms.