Not directly relevant, but another good sci-fi about genetics — Daniel Suarez' Change Agent.
davew On Sun, Apr 19, 2020, at 10:41 AM, Steven A Smith wrote: > Marcus - > > > I believe that Andrew Niccol DID imagine something like that: > > I wish I had a pithy preamble for this dystopian BioPunk reference, but > perhaps it speaks for itself? > >> https://en.wikipedia.org/wiki/Gattaca > > - Steve >> Steve writes: >> >> < The whole world is responding to what is *roughly* the same virus with >> *roughly* what is the same human phenotype/metabolism in a myriad of >> *roughly* the same modes of human organization. > >> >> There are hundreds of common HLA alleles across humans. In a diverse country >> like the US, with hundreds of thousands of positive cases and tens of >> thousands of deaths the hundreds of alleles would be well sampled. Too bad >> our medical surveillance is so bad, and made worse by the moron. Imagine if >> everyone had full genome sequencing and every viral sample was deep >> sequenced. >> >> Marcus >> >> *From:* Friam <friam-boun...@redfish.com> on behalf of Steven A Smith >> <sasm...@swcp.com> >> *Sent:* Sunday, April 19, 2020 10:11 AM >> *To:* friam@redfish.com <friam@redfish.com> >> *Subject:* Re: [FRIAM] Judea Pearl: Book of Why >> >> >>> One way to address the N/A issue is to repeatedly perturb the real-world >>> system so as to elicit those correlations. When that is practical.. >> >> We are, in a time of real-world system perturbation, right now. The whole >> world is responding to what is *roughly* the same virus with *roughly* what >> is the same human phenotype/metabolism in a myriad of *roughly* the same >> modes of human organization. This IS a testbed of human (-system?) response >> to a widespread, somewhat invisible threat. From Wuhan to Singapore to Italy >> to Iran to Sweden to Germany to NYC to WA State to the Navajo Nation to >> Florida's beaches, this IS a huge coupled systems dynamics/agent-model >> executed in real-time by real-people with real casualties and real >> consequences. >> We are, to varying degrees (collectively) recording the results of these >> "experiments" and if we are lucky (or smart, or both) we will do some >> post-game analysis intended to understand more-better how best to >> (self-)organize around a (nearly) existential world-scale threat. And to the >> extent this is a game that will never end, we have to begin the analysis >> while we cope with it's consequences. Feels a bit like the models pof >> Physics Interreality. >> https://journals.aps.org/pre/abstract/10.1103/PhysRevE.75.057201 >> Hanging too aggressive of a model on this (or collecting the data against >> too premature of a model) will reduce the utility of such data gathering and >> analysis. Whatever the dual of overfitting a model is? Overmodeling? >> Premature Modeling? >> What I'm looking (askance) to(ward) Pearl for is a better way of rapidly >> constructing, maintaining, revising as generic of a model as possible in >> response to "this moment". Four months ago we should have been interested in >> models of how one limits a virus such as COVID19 getting a foothold in this >> country. One month ago we should have been interested in how one limits >> COVID19 (with new understanding of it's virility, it's fatality, it's >> symptoms, it's mode of spread) once it HAS a foothold, now we are faced with >> trying to understand how to cope with it once it is pervasive in our >> population whilst continuing/returning to "business as usual" and in another >> thread, I'm encouraging that we "try to plan/consider/think-about" what we >> want to do with this somewhat "blank slate" (our ass?) we are having handed >> to us. >> And how to think about this without premature modeling... what I think I was >> railing (whining/pushing-back) about with Dave on the Bellamyist thread >> earlier this morning. >> - Steve >>>> On Apr 19, 2020, at 8:33 AM, uǝlƃ ☣ <geprope...@gmail.com> wrote: Well, the argument I often end up making is that you can do a kind of face validation with the fake data. Show it to someone who's used to dealing with that sort of data and if the fake data looks a lot like the data they normally deal with, then maybe more data-taking isn't necessary. If it looks fake to the "expert", then more data-taking is definitely needed. >>>> >>>>> On 4/19/20 8:29 AM, Marcus Daniels wrote: I have a hard time with this as a way to extend data. If it is high-dimensional it will be under-sampled. Seems better to me to measure or simulate more so that the joint distribution can be realistic. And if you can do that there is no reason to infer the joint distribution because you *have* it. >>>>> >>>>>>> On Apr 19, 2020, at 8:18 AM, Frank Wimberly <wimber...@gmail.com> wrote: >>>>>>> >>>>>> Going back and forth: If you infer the causal graph from observational data you can use that graph to simulate data with the same joint distribution as the original data. >>>>>> >>>> -- ☣ uǝlƃ .-. .- -. -.. --- -- -..-. -.. --- - ... -..-. .- -. -.. -..-. -.. .- ... .... . ... 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