To date, BenchSci’s machine learning algorithm has decoded millions of Open Access scientific papers and over 3.7 million antibody products. However, OA papers only represent a subset of all scientific literature. Scientists generally use resources like Google or Pubmed, and are missing out on tools and other resources that publishers might offer. BenchSci therefore has initiated talks with publishers to make their content discoverable through BenchSci without a loss of readership or traffic to their sites.

We are happy to announce our official collaboration with the Federation of Societies for Experimental Biology (FASEB) with the inclusion of The FASEB Journal on our platform!

The FASEB Journal (FJ), the flagship publication of the Federation of American Societies for Experimental Biology (FASEB), is highly cited and consistently ranks among the top biology journals globally. Each month, FJ publishes peer-reviewed, multidisciplinary original research articles as well as timely editorials, reviews, and news of the life sciences. As disciplines in the life sciences continue to overlap, readers are drawn to the journal for its trans-disciplinary coverage.

The journal has been covered by major news outlets, such as The New York Times, The Washington Post, The Chicago Tribune, U.S. News and World Report, Reuters, National Public Radio, Voice of America, ABC News, Scientific American, Bloomberg News, MSNBC, and BBC News.

Why is BenchSci a game-changer?

“Publish or perish” is a driving force for scientists, but funding resources are limited. They need to find the right products for their research, and fast. BenchSci prevents a waste of time and resources by bringing scientists to the relevant information they need in a fraction of the time.

BenchSci is aiming to create a community between publishers, scientists and suppliers to allow scientists to have all the information they need in one place, allowing them to design superior experiments by making use of result sets to make informed decisions.

What will content look like on BenchSci?

BenchSci does not contain full text content on its platform. BenchSci’s machine learning technology pinpoints the exact information scientists are looking for within the paper, and displays the figures for them to choose. The figures act as a window into the published article, giving scientists more confidence that the information relevant to their search parameters is located within the paper. Once they find the paper they would like to explore further, they are redirected back to the publisher website to access the full text.

The partnership between BenchSci and FASEB is a great first step to generating a more comprehensive database and allowing scientist to harness the power of the BenchSci platform to accelerate the pace of their research!

If you are a publisher that is interested in our free indexing service please contact us at

Sign Up and Search Antibodies Now BenchSci uses machine learning to decode  published data and  present figures with actionable, experiment-specific insights. Learn More

Written By:
Casandra Mangroo