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> Out of curiosity, does your UI allow any form of "simulation", particularly a random fuzzing/monte carlo trials? No, at the moment we don't really have enoug

> Out of curiosity, does your UI allow any form of "simulation", particularly a random fuzzing/monte carlo trials? No, at the moment we don't really have enough structured knowledge of the underlying steps to be able to do predictions/simulations like that. We're taking existing scientific workflows and adding structure to them, but there are still plenty of details that are unstructured and performed manually by scientists, and there's a lot of variability across use cases. Monte carlo trials certainly seems interesting, though, and hopefully something we can explore more as the procedures get more structured. A similar idea that's a bit closer in reach is to do an analysis on past variations of the same experiment to predict how a newly-designed experiment will go. Possibly we could do a simulation based on historical data like that, although modeling it correctly certainly sounds tricky.

elcritch 9y ago
> We're taking existing scientific workflows and adding structure to them, but there are still plenty of details that are unstructured and performed manually by scientists, and there's a lot of variability across use cases. That makes sense. It’s difficult to start adding structure to biological sciences. And to the fields credit I don’t think it’s out of lack of ability or effort but just the true complexity of dealing with biological systems. In contrast, even quantum mechanics is seemingly simple! > Possibly we could do a simulation based approach on historical data like that, although modeling it would correctly certainly sounds tricky. True, seems like you will have a very valuable historical dataset though. I’ve been pondering this type of problem for a few years since my (abortive) attempt at a PhD in material sciences. For my project I made some decent progress using various Bayesian and bootstrapping models to work with uncertainty in my models and tissue samples. Bayesian approaches, especially combined with MCMC type analysis can yield a lot of fruit dealing with biological systems with minimal need to understand the underlying models. But as you mention modeling the parameters correctly is challenging and there’s a lacunae in research broaching the topic. But at the least a system like yours could indicate items like conditional probability of failure given certain sequence sets or combinations of experimental procedures (e.g. cell lines A tend to do better when cultured in X media and tested with Y +/- Z hours). The article seems to indicate you’d have most of the data described in a format that’d be amendable to such data mining.

elcritch 9y ago

> We're taking existing scientific workflows and adding structure to them, but there are still plenty of details that are unstructured and performed manually by scientists, and there's a lot of variability across use cases. That makes sense. It’s difficult to start adding structure to biological sciences. And to the fields credit I don’t think it’s out of lack of ability or effort but just the true complexity of dealing with biological systems. In contrast, even quantum mechanics is seemingly simple! > Possibly we could do a simulation based approach on historical data like that, although modeling it would correctly certainly sounds tricky. True, seems like you will have a very valuable historical dataset though. I’ve been pondering this type of problem for a few years since my (abortive) attempt at a PhD in material sciences. For my project I made some decent progress using various Bayesian and bootstrapping models to work with uncertainty in my models and tissue samples. Bayesian approaches, especially combined with MCMC type analysis can yield a lot of fruit dealing with biological systems with minimal need to understand the underlying models. But as you mention modeling the parameters correctly is challenging and there’s a lacunae in research broaching the topic. But at the least a system like yours could indicate items like conditional probability of failure given certain sequence sets or combinations of experimental procedures (e.g. cell lines A tend to do better when cultured in X media and tested with Y +/- Z hours). The article seems to indicate you’d have most of the data described in a format that’d be amendable to such data mining.