Antibodies are one of the most commonly used research reagents. However, due to their innate variability, finding the right antibody can be a challenge. Scientists devote a significant amount of time sifting through the literature to find antibodies that have been shown to work under specific experimental contexts matching their research interests. This process often takes several hours, sometimes even days, wasting valuable time that could otherwise be used more efficiently.
BenchSci has created a solution to this problem by developing a machine-learning algorithm that decodes primary research papers to identify the antibody used and the associated experimental contexts in each paper. Scientists can search their protein of interest on BenchSci’s open-access online platform, and find results displayed in the form of individual figures from scientific papers in which antibodies against that protein were used. These figures are easily filterable to allow users to narrow down their search results to the antibody use cases that best fit their experimental contexts and, ultimately, find the best antibodies for their experiments.
On the open-access BenchSci platform, we have developed several features that can facilitate evidence-based antibody selection. Check them out below!
1. Search results can be viewed as “Figures” or “Products” list
Depending on your preference, you may wish to examine figures first then identify the antibody used, or you may wish to examine antibodies first then view associated figures that supported its use.
2. Figures and Products can be filtered by specific experimental contexts
Using filters such as Techniques, Tissue, and Cell Lines, and more, you can easily identify published figures and the antibody used that match your experimental interest in seconds.
3. Direct link to original paper and antibody supplier
If you found a figure or product of interest, you can directly link to the original paper or the supplier website, respectively.
4. Save Figures and/or Products to “My Bench”
For individual figures or products of your interest, you can track them by saving to folders in “My Bench”.
Within My Bench, you can organize the figures and products into different project folders.
5. Submit Reviews for your (least) favourite antibody
Data that proves an antibody didn’t work under certain contexts is equally important as data that showed the antibody worked. Unfortunately, this information is not captured anywhere else other than in your lab notebook.
The Review function is where you can let fellow scientists know that you have tested a certain antibody, and whether or not it worked as intended.
6. Sharing the knowledge
You can email individual figures or products to your colleagues, labs members, or collaborators with the click of a button.
We would like to invite you to create a free academic account at www.BenchSci.com, and experience how efficient evidence-based antibody selection can be!
For any questions, suggestions, or comments, please get in touch with Maurice (email@example.com). We would love to hear from you.