Remove the Barriers

Biology is rapidly becoming a data-driven science. With the explosion of single-cell sequencing, spatial imaging, and high-throughput functional assays, modern biological research often begins not at the bench, but with a hard drive full of data. But alongside this transformation, a new set of barriers has emerged—ones that quietly shape who gets to participate in discovery.

Barrier 1: Tools are powerful, but not always accessible.

Biologists often have sharp insights—creative hypotheses, unexpected connections, a sense of what might matter in a sea of noise. But turning those ideas into action increasingly requires coding skills. Even with the help of AI, which can generate scripts and automate workflows, many biologists find themselves stuck. The learning curve is steep, and the tools aren’t always transparent. On the other hand, data scientists may bring computational power but sometimes apply machine learning in a way that feels disconnected—turning rich biological questions into AI black boxes. When neither side can fully bridge the gap, important insights risk being lost in translation.

Barrier 2: The opportunity to do research is still limited.

Despite the growing importance of big data and AI in biology, access to research remains largely gated. Graduate students and postdocs are the primary engines of discovery in most labs. Meanwhile, high school and undergraduate students—with curiosity, time, and often surprising talent—are left waiting for a “right time” that may never come. The message is rarely explicit, but it’s there: the tools are too complex, the stakes too high. But if we really want innovation, we need to lower the barrier to entry. Talent doesn’t wait for a PhD.

If biology is to benefit from its ongoing data revolution, we need to think beyond the data itself. That means building more intuitive tools, offering mentorship and early exposure, and designing systems that allow great ideas—regardless of where they come from—to be tested, refined, and shared. Discovery should be challenging, yes. But not exclusive.

Can we open the box for everyone?