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Thanks for providing well thought-through advice like that. Following your arguments it seems pretty clear to me that you put a lot of thought in that. If I ma

Thanks for providing well thought-through advice like that. Following your arguments it seems pretty clear to me that you put a lot of thought in that. If I may ask, what's your background that tells you things like "most CS folks understand MB and find genetics confusing"?

dekhn 7y ago
My background is dual CS and MB. In particular, I got an undergraduate degree in Molecular Biology at UCSC and did my undergraduate thesis with David Haussler (CS professor who helped "save the human genome") on probabilistic graphical models of E.Coli genes. At that time I didn't really know much CS (just hacking), so I went into grad school (BIophysics PhD) but focused on computational chemistry, so got lots of fortran distributed computing programming experience. Based on that I was able to do a couple postdocs in bioinformatics, increasing my understanding of protein function and evolution, and then became a full-time scientist, however after several years of not being able to find funding, went to work at Google for a decade where I taught myself all the CS I didn't previously know and applied it to scientific computing. Now I work for a company that does machine learning for drug discovery. What I've learned over the years is that genetics is a field where people who excel in abstract thinking about blobby, messy, wet objects succeed and understand the paradigms. While CS people find molecular biology, with its concerete focus on molecular entities (agents) interacting is very easy to understand. After many years of trying to understand genetics I finally realized that many of the paradigms in genetics are just useful but wrong models that don't correspond to reality.
- Infinitesimus 7y ago
  (Not OP) Woah, thanks for the detailed answer and your perspective on this thread. I'm very guilty of thinking "don't we have enough approximations to brute force some solutions to problems in some parts of biology yet?" and your comment have helped provide some context that these are _hard_ problems and we are still gathering information to form better models in a lot of cases. If you dont mind me asking, where so you work? (Happy to take it to a private channel as well if you prefer )
- abledon 7y ago
  What do you think of ancient attempts at medical models involving bio-electric energy regulating bodily functions (e.g. chi/prana)? Do you think we have a long ways to go in reconciling modern science to ancient observations?
  - kr4 7y ago
    It's considered possible to stop aging with a strict yogic lifestyle. Requires a sincere study to verify and learn from such ancient systems.

dekhn 7y ago

My background is dual CS and MB. In particular, I got an undergraduate degree in Molecular Biology at UCSC and did my undergraduate thesis with David Haussler (CS professor who helped "save the human genome") on probabilistic graphical models of E.Coli genes. At that time I didn't really know much CS (just hacking), so I went into grad school (BIophysics PhD) but focused on computational chemistry, so got lots of fortran distributed computing programming experience. Based on that I was able to do a couple postdocs in bioinformatics, increasing my understanding of protein function and evolution, and then became a full-time scientist, however after several years of not being able to find funding, went to work at Google for a decade where I taught myself all the CS I didn't previously know and applied it to scientific computing. Now I work for a company that does machine learning for drug discovery. What I've learned over the years is that genetics is a field where people who excel in abstract thinking about blobby, messy, wet objects succeed and understand the paradigms. While CS people find molecular biology, with its concerete focus on molecular entities (agents) interacting is very easy to understand. After many years of trying to understand genetics I finally realized that many of the paradigms in genetics are just useful but wrong models that don't correspond to reality.

Infinitesimus 7y ago
(Not OP) Woah, thanks for the detailed answer and your perspective on this thread. I'm very guilty of thinking "don't we have enough approximations to brute force some solutions to problems in some parts of biology yet?" and your comment have helped provide some context that these are _hard_ problems and we are still gathering information to form better models in a lot of cases. If you dont mind me asking, where so you work? (Happy to take it to a private channel as well if you prefer )
abledon 7y ago
What do you think of ancient attempts at medical models involving bio-electric energy regulating bodily functions (e.g. chi/prana)? Do you think we have a long ways to go in reconciling modern science to ancient observations?
- kr4 7y ago
  It's considered possible to stop aging with a strict yogic lifestyle. Requires a sincere study to verify and learn from such ancient systems.