A free program that allows scientists to find antibody usage data in published figures has been added to the researcher tools section of the Office for Research website.
Founded in 2015, BenchSci relies on machine learning software that reads papers like a scientist, extracting figures to understand the context around them, such as specific techniques, tissues, and disease used in the experiment. The result is a massive database aimed at accelerating scientific discovery. See how it works here.
The artificial intelligence-driven search has decoded millions of scientific papers and extracted more than 820,000 antibody usages in the form of published figures. Users are able to view more than 2,100,000 images from vendors, independent organizations, and reviewers.
“BenchSci allows researchers to share their experiences with antibodies regardless of whether they plan to publish the results,” says Phil Hockberger, assistant vice president for research. “This will be a game changer for biomedical researchers by contributing to antibody authentication, a major concern of the National Institutes of Health (NIH) Rigor and Reproducibility initiative.”
In 2014 NIH held a joint workshop with the Nature Publishing Group and Science to consider issues of reproducibility and rigor in research findings. The workshop focused on identifying common opportunities in the scientific publishing arena to enhance rigor and further support research that is reproducible, robust, and transparent. Antibody authentication continues to be one of the major topics of the Rigor and Reproducibility initiative and universities are continuing to address NIH guidelines with regard to how training should be handled.