Innovative science frequently occurs as a result of cross-disciplinary collaboration, the importance of which is reflected by recent NIH funding initiatives that promote communication and collaboration. If shared research interests between collaborators are important for the formation of collaborations, methods for identifying these shared interests across scientific domains could potentially reveal new and useful collaboration opportunities. MEDLINE represents a comprehensive database of collaborations and research interests, as reflected by article co-authors and concept content. We analyzed six years of citations using information retrieval-based methods to compute articles’ conceptual similarity, and found that articles by basic and clinical scientists who later collaborated had significantly higher average similarity than articles by similar scientists who did not collaborate. Refinement of these methods and characterization of found conceptual overlaps could allow automated discovery of collaboration opportunities that are currently missed
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