History
"What if you could search biology?” It’s ostensibly a very simple question. After all, we have years, decades even, of searchability in many parts of our lives. In less than ten seconds you can easily find the five closest coffee shops to your current location, because a number of organizations have created digital maps of the world, identified and labeled objects like “coffee shop” on those maps, and made these maps easily accessible to anyone with an internet connection.
Biology has been much harder to search. This is true for many reasons: it’s incredibly complex, we don’t always know what we’re measuring and if it’s relevant, we don’t have consistent labels like “coffee shop” across datasets, there isn’t a centralized organization that indexes all of this complex data in one accessible place, etc. Our team has lived this problem in many contexts: trying to make sense of high-complexity biological datasets while in academia; building searchability across other datasets at large technology companies; poring through disparate, unstructured, un-linked datasets to guide an investment decision around a therapeutic target.
