The NIDDK Information Network ( is a portal for basic and clinical investigators that makes it easier to discover, obtain, and reuse scientific research resources. Here we demonstrate how dkNET can connect researchers to resources for obesity research. A search for “obesity” returns 264,498 results (Table 1), including physical resources (i.e., antibodies, cell lines, model organisms), digital resources, data, models, funding, and knowledge bases. dkNET facilitates discovery not only within well known databases like GEO, Mouse Phenome Database, or model organism databases such as MMRRC, but also many unique but less well known databases, such as Animal Quantitative Trait Loci or Aging Gene/Interventions databases. dkNET provides some basic analytic tools, e.g., word clouds, category graphs, to aid exploration. dkNET provides in depth information on how resources are used through Research Resource Identifier (RRID), a unique ID allowing dkNET to aggregate and provide information, e.g., about known problems with antibodies or cell lines. To assist researchers in complying with NIH guidelines on rigor and transparency, dkNET provides a tool to suggest authentication plans for key research resources. dkNET also provides reports to track resource utilization. These new services aim to not only enhance transparency of research but also ensure that resource creators are appropriately credited.


K. Lin: None. A. Bandrowski: None. J. Go: None. I. Ozyurt: None. T. Gillespie: None. J.S. Grethe: None. M.E. Martone: None.

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