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Database of NIH grants using machine-learned categories and graphical clustering

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Figure 1: Graphically clustered NIH grants, as rendered from a screenshot of the NIHMaps user interface.

Acknowledgements

We acknowledge assistance and support from G. LaRowe and N. Skiba at ChalkLabs, and input and feedback from NIH staff during the project. We thank S. Silberberg, C. Cronin, K. Boyack and K. Borner for helpful advice and comments on the manuscript. This project has been supported through small contracts from the NIH to University of Southern California (271200900426P and 271200900244P), University of Massachusetts (271201000758P, 271200900640P, 271201000704P and 271200900639P), ChalkLabs LLC (271200900695P and 271201000701P) and TopicSeek LLC (271201000620P and 271200900637P).

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Correspondence to Edmund M Talley.

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B.W.H. II is employed by Chalklabs, LLC, which was contracted for a portion of the work described in the report. D.N. is owner of TopicSeek, LLC, which was also contracted for a portion of the described work.

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Supplementary Figure 1, Supplementary Data, Supplementary Methods (PDF 1409 kb)

Supplementary Table 1

Categories of machine-learned topics and their potential NIH institute representations for grants from funding year 2009. (PDF 2133 kb)

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Talley, E., Newman, D., Mimno, D. et al. Database of NIH grants using machine-learned categories and graphical clustering. Nat Methods 8, 443–444 (2011). https://doi.org/10.1038/nmeth.1619

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