@AlexanderKalian: Biology has an exteme lack of data, relative to what AI needs - I am sorry to say. I am not sure how anyone can claim o…

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Summary

Alexander Kalian argues that biology lacks sufficient high-quality data for AI, while César de la Fuente counters that data exists but needs better organization, highlighting the AllTheBacteria preprint as an open platform for bacterial genomes.

Biology has an exteme lack of data, relative to what AI needs - I am sorry to say. I am not sure how anyone can claim otherwise. For example, there are tens of thousands protein targets relevant to human disease. Our data on what binds to each is <20 data points, for most. It's also overwhelmingly biased to things that strongly bind, rather than things which don't. Deep learning models for molecules binding to a particular target typically need ~1,000+ data points for training, to generalise well onto new data. Deep learning models also need balance in training data. And don't get me started on data relevant to ADME, metabolites, downstream pathways, protein-protein interactions, different proteoforms, epigenetics, toxicology etc.
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Cached at: 07/22/26, 06:35 PM

Biology has an exteme lack of data, relative to what AI needs - I am sorry to say.

I am not sure how anyone can claim otherwise.

For example, there are tens of thousands protein targets relevant to human disease. Our data on what binds to each is <20 data points, for most.

It’s also overwhelmingly biased to things that strongly bind, rather than things which don’t.

Deep learning models for molecules binding to a particular target typically need ~1,000+ data points for training, to generalise well onto new data.

Deep learning models also need balance in training data.

And don’t get me started on data relevant to ADME, metabolites, downstream pathways, protein-protein interactions, different proteoforms, epigenetics, toxicology etc.

César de la Fuente (@delafuentelab): Biology has no shortage of data. The challenge is to organize it well enough that scientists—and machines—can learn from it.

Our latest preprint presents AllTheBacteria: an open, community-built platform that transforms 2.44 million public bacterial and archaeal genomes into a

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