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The ability to actually reprogram cancer cells relates to... >our fundamental constitution as multicellular organisms, our limited lifespan, the epidemiology o

The ability to actually reprogram cancer cells relates to... >our fundamental constitution as multicellular organisms, our limited lifespan, the epidemiology of the aging population, socioeconomics and the future of society. Like, hey man, you do realize that the killing or reprogramming of cancer cells goes far beyond the molecular technicalities of actually doing it? Yup. It’s a pretty vacuous critism.

devereaux 8y ago
Medical technology is lacking. With sequencing, we have a very hard-to-use, slow and readonly hexedit. With crispr, we have a very buggy and feature incomplete sed -- more like ed actually. It cool to have some sed, but we may not even need that. We just need the equivalent of basic modern unix tools, like find, grep and rm, that work reliably, with good specificity and sensitivity. Yet basic unix tools in medicine are decades away. Maybe it will be nanotechnology, maybe it will be more hacking around current solution. Still, the problem is just: find /body -type cancer_12BA |grep -v cancer_12BA_market_but_usefull_stemcell |xargs rm The solution is technological, not philosophical.
- zackmorris 8y ago
  Ya making a transform to go between the physical abstractions in biology/chemistry and the data abstractions in computer science should be top priority. Frankly, I don't see how biochemists today could possibly keep up with the advancements in AI and big data that have happened in just the last few years (and vice versa). I'd like to see everyone take a step back and look at treating cancer as solving a large matrix where no single cause leads to an outcome. We need genetic algorithms to quickly find local maximums and minimums, we need machine learning to see correlations between seemingly unrelated findings, we need better standards for getting longterm studies into formats that are easily grokked by AI. These are all straightforward, but I sense that there may be some resistance from the medical community in opening up the research similar to something like Folding@home. And in fairness, medical researchers are doing the heavy lifting. The first step probably has to come from hackers in the data science community, working with existing public research, and they're going to need real funding (which may not come until after the first of many cures is spotted).
- Wowfunhappy 8y ago
  Your crispr = sed analogy is apt because DNA is basically code. Cells, however, are not files, so I would be careful extending the analogy. There is no "find" command for the same reason you can't run "find" on your physical bookshelf--objects in 3d space are not indexable files on a hard drive. Perhaps we'll eventually have microscopic robots that can search out specific cells, in the same way Amazon uses robots to retrieve items in their warehouses. But that's a very different problem space, where the focus is largely mechanical rather than programmatic.

devereaux 8y ago

Medical technology is lacking. With sequencing, we have a very hard-to-use, slow and readonly hexedit. With crispr, we have a very buggy and feature incomplete sed -- more like ed actually. It cool to have some sed, but we may not even need that. We just need the equivalent of basic modern unix tools, like find, grep and rm, that work reliably, with good specificity and sensitivity. Yet basic unix tools in medicine are decades away. Maybe it will be nanotechnology, maybe it will be more hacking around current solution. Still, the problem is just: find /body -type cancer_12BA |grep -v cancer_12BA_market_but_usefull_stemcell |xargs rm The solution is technological, not philosophical.

zackmorris 8y ago
Ya making a transform to go between the physical abstractions in biology/chemistry and the data abstractions in computer science should be top priority. Frankly, I don't see how biochemists today could possibly keep up with the advancements in AI and big data that have happened in just the last few years (and vice versa). I'd like to see everyone take a step back and look at treating cancer as solving a large matrix where no single cause leads to an outcome. We need genetic algorithms to quickly find local maximums and minimums, we need machine learning to see correlations between seemingly unrelated findings, we need better standards for getting longterm studies into formats that are easily grokked by AI. These are all straightforward, but I sense that there may be some resistance from the medical community in opening up the research similar to something like Folding@home. And in fairness, medical researchers are doing the heavy lifting. The first step probably has to come from hackers in the data science community, working with existing public research, and they're going to need real funding (which may not come until after the first of many cures is spotted).
Wowfunhappy 8y ago
Your crispr = sed analogy is apt because DNA is basically code. Cells, however, are not files, so I would be careful extending the analogy. There is no "find" command for the same reason you can't run "find" on your physical bookshelf--objects in 3d space are not indexable files on a hard drive. Perhaps we'll eventually have microscopic robots that can search out specific cells, in the same way Amazon uses robots to retrieve items in their warehouses. But that's a very different problem space, where the focus is largely mechanical rather than programmatic.