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In our first episode of The Next Experiment, we start by unpacking that all-important question:  Why is biology so hard?  In order to answer it, we get into the fundamentals. The nature of nature.  We talk about how biology’s interconnectedness makes experimentation in biology so uncertain; why …
If data is the new oil in an AI centric world, then amassing ever-larger multidimensional datasets can only be a good thing.  But how can we use these datasets to gain deeper insight into biology? This is the question we try to answer in season 1’s final episode. Between us, we bring views of the…
To explore what the future of multidimensional experiments might look like, we decided to look back. In this episode, we explored how different multi-dimensional (aka Design of Experiments, or DOE) methods have come about to date.  Then, we pondered how these different methods, together with …
It’s easy to say that the tried-and-tested way of doing biology isn’t helping us progress. It’s quite another to embrace new approaches.  That’s what we’re covering in this second episode. We talk about communicating the power of multidimensional experimentation for biology, the insights they unl…
In this episode, we delve into Markus’ experiences with doing multidimensional biological experiments manually—from the exhilarating progress he made, to the definitive results he produced. Plus, we touch on how automation can scale multidimensional experimentation, and when is the right time to b…
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