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Abstract:
The evidence that two molecules interact in a living cell is often
inferred from multiple different experiments. Experimental data is
captured in multiple repositories, but there is no simple way to assess
the evidence of an interaction occurring in a cellular environment.
Merging and scoring of data are commonly required operations after
querying for the details of specific molecular interactions, to remove
redundancy and assess the strength of accompanying experimental
evidence. We have developed both a merging algorithm and a scoring
system for molecular interactions based on the proteomics standard
initiative-molecular interaction standards. In this manuscript, we
introduce these two algorithms and provide community access to the tool
suite, describe examples of how these tools are useful to selectively
present molecular interaction data and demonstrate a case where the
algorithms were successfully used to identify a systematic error in an
existing dataset.
