4 ms·

Virtual cells

124 points by surprisetalk 1y ago

nextos 1y ago
UConn coordinated a ton of work during the past two decades on mechanistic cell models. Mostly ODEs, PDEs, and stochastic ODEs. See The Virtual Cell at https://vcell.org https://vcell.org. It's interesting how high-throughput perturbation assays have led to data-driven whole cell models. But these are not yet good at making robust predictions. Probably the future are hybrid neuro-symbolic models.
- donovanr 1y ago
  Yes, this. A lot of work in this field is missing from that timeline. Just circa 2010-2020, Les Loew's VCell 3D PDE approaches, Faeder et al.'s BioNetGen / ODE work, Luthey-Schulten Shulten's grid based cell models, the Pittsburgh supercomputing center's 3D monte-carlo MCell, the image-based deep learning models at the Allen Institute for Cell Science... It's nice to see the idea of virtual cells make a comeback now, though the meaning seems to have shifted to transciptomics-based transformer / gpu-powered models (which have issues[0]), it's a fun field / problem, but I think it will make better progress if we take advantage of all the varied computational work that has come before. [0] Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them all https://arxiv.org/abs/2410.13956 https://arxiv.org/abs/2410.13956
  - udara 1y ago
    oh that's interesting, I didn't come across these the way I was looking at it! thank you for informing us, I will read up on these and add it to the timeline!
- paulfharrison 1y ago
  What a strange web page. Scrolling is thoroughly broken. I recently went to a two day workshop on whole cell modelling. I'm still trying to work out how much of the exercise is fantasy. I get that some of the chemistry is well enough understood to simulate from the ground up, but there's so much more to it. The oddest thing to me is the level of satisfaction in being able to run the model. I would think the model has to be very very fast, because of all the work that needs to be done with it to fit it to data and fully understand its behavior.
  - jdonaldson 1y ago
    Lol! Overriding basic scroll functionality on esoteric cell simulation software documentation pages is such a pointless gamble. Really calls the quality of the software itself into question.
deleted 1y ago
[deleted]
hobofan 1y ago
While it says this: > By 2021, these engineered bacteria could be simulated in unprecedented detail. Every gene, every major protein, and nearly every metabolic reaction in JCVI-syn3A. I think the crux is here: > Even after years of study, 91 of JCVI-syn3A's genes remain unannotated, of which roughly one-third are essential. Deleting any single one kills the cell, yet we have no idea what they do – representing some of biology's most fundamental unsolved puzzles. --- I think minimal cells and virtual cells are especially exciting as they open up a path to create fully controlled experimental environments for biochemistry from the ground up. Right now sooo much time in biochemistry goes into working around the limitations of what already happens to be present in an organism. E.g. we may know 5% of mechanisms that go on in a cell, but the remaining 95% percent of mechanisms that go on may still brick your experiment, and without knowing about them you essentially have to shrug and trial and error your way through them. In contrast in a synthetic minimal cell, we could start out with an organism where we know 95% of the mechanisms that are going on, and then study new mechanisms one gene at a time, steadily building up to bigger and bigger mechanisms. Strangely it seems to me that a lot of effort is going more into being able to simulate full cells that contain unknown mechanisms, rather than trying to use the capabilities to create hypothesis to uncover the unknown mechanisms. Yes, that probably expedites the path towards simulating much bigger human cells, but ultimately still leaves us in the dark on most fronts.
- suddenlybananas 1y ago
  >Strangely it seems to me that a lot of effort is going more into being able to simulate full cells that contain unknown mechanisms, rather than trying to use the capabilities to create hypothesis to uncover the unknown mechanisms. Yes, that probably expedites the path towards simulating much bigger human cells, but ultimately still leaves us in the dark on most fronts. Seems the result of this general trend in science towards brute prediction and abandoning the goal of explanation or understanding.
  - filoeleven 1y ago
    Check out Michael Levin’s lab for a refreshing and amazing example of a group that’s bucking the trend. They are doing tons of experiments by starting with the premise that cells and their networks have intelligence, then using tools from behavioral science to convince them to do what the experimenters want (e.g. “grow an eye here”). I’ve been convinced by Levin’s talks that this is a more promising area of research than genetics. https://drmichaellevin.org/ https://drmichaellevin.org/
moralestapia 1y ago
Great post. This is exactly what I'm an expert at, I even coined a term in the field [1], :). Since I started doing this 15 years ago (and I know the field predates me by much), one always has had this feeling that we are so close to a big breakthrough in biological simulation, but at the same time, progress has been kind of "slow". I think the reason for that is because pushing the envelope forward in this field requires mastering three (maybe four) different disciplines, your pick of [Bio, Chem, CS, Math, Physics]. Very few people reach this level of simultaneous understanding of all these pieces. I'm not trying to gatekeep the field, though, much of the progress here (including many of the papers mentioned in TFA) is work coming from PhD students. Anyone could jump into this, but you really need to sit down and try to make sense of it for a while, years. PhD gives one the perfect opportunity for that. Anyway, I hope this thing keeps going on forward, it's one of the ultimate goals of Biology and it would be extremely beneficial to the world. 1: https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2016.01881/full https://www.frontiersin.org/journals/plant-science/articles/...
- _factor 1y ago
  Thank you for your contributions. You are quite literally saving lives. Are there any good local (op-so ideally) tools and/or libraries one can experiment with? I have access to a couple HPC clusters and would love to learn more.
  - moralestapia 1y ago
    Sure! Take a look at SimTK [1]. And I would try to reproduce Karr's model [2], paper here [3]; also mentioned in the linked page. This is the study that made me, and many others at the time, to actually take this seriously, lol. I was a student and was doing this as a hobby project, Karr's paper made me think "wait, this is actually possible, and today". It's really good if you want to learn and get your feet wet on this. If you want, you can reach out to me at hn @ moralestapia . com, and I'll be happy to recommend some more stuff! 1: https://simtk.org/ https://simtk.org/ 2: https://simtk.org/projects/wholecell https://simtk.org/projects/wholecell 3: https://www.cell.com/cell/fulltext/S0092-8674(12)00776-3 https://www.cell.com/cell/fulltext/S0092-8674(12)00776-3
maltee 1y ago
Great article! Also, really nice site design, the referenced papers and annotations are a really nice touch!

124 points by surprisetalk 1y ago

UConn coordinated a ton of work during the past two decades on mechanistic cell models. Mostly ODEs, PDEs, and stochastic ODEs. See The Virtual Cell at https://vcell.org https://vcell.org. It's interesting how high-throughput perturbation assays have led to data-driven whole cell models. But these are not yet good at making robust predictions. Probably the future are hybrid neuro-symbolic models.

donovanr 1y ago
Yes, this. A lot of work in this field is missing from that timeline. Just circa 2010-2020, Les Loew's VCell 3D PDE approaches, Faeder et al.'s BioNetGen / ODE work, Luthey-Schulten Shulten's grid based cell models, the Pittsburgh supercomputing center's 3D monte-carlo MCell, the image-based deep learning models at the Allen Institute for Cell Science... It's nice to see the idea of virtual cells make a comeback now, though the meaning seems to have shifted to transciptomics-based transformer / gpu-powered models (which have issues[0]), it's a fun field / problem, but I think it will make better progress if we take advantage of all the varied computational work that has come before. [0] Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them all https://arxiv.org/abs/2410.13956 https://arxiv.org/abs/2410.13956
- udara 1y ago
  oh that's interesting, I didn't come across these the way I was looking at it! thank you for informing us, I will read up on these and add it to the timeline!
paulfharrison 1y ago
What a strange web page. Scrolling is thoroughly broken. I recently went to a two day workshop on whole cell modelling. I'm still trying to work out how much of the exercise is fantasy. I get that some of the chemistry is well enough understood to simulate from the ground up, but there's so much more to it. The oddest thing to me is the level of satisfaction in being able to run the model. I would think the model has to be very very fast, because of all the work that needs to be done with it to fit it to data and fully understand its behavior.
- jdonaldson 1y ago
  Lol! Overriding basic scroll functionality on esoteric cell simulation software documentation pages is such a pointless gamble. Really calls the quality of the software itself into question.

deleted 1y ago

[deleted]

hobofan 1y ago

While it says this: > By 2021, these engineered bacteria could be simulated in unprecedented detail. Every gene, every major protein, and nearly every metabolic reaction in JCVI-syn3A. I think the crux is here: > Even after years of study, 91 of JCVI-syn3A's genes remain unannotated, of which roughly one-third are essential. Deleting any single one kills the cell, yet we have no idea what they do – representing some of biology's most fundamental unsolved puzzles. --- I think minimal cells and virtual cells are especially exciting as they open up a path to create fully controlled experimental environments for biochemistry from the ground up. Right now sooo much time in biochemistry goes into working around the limitations of what already happens to be present in an organism. E.g. we may know 5% of mechanisms that go on in a cell, but the remaining 95% percent of mechanisms that go on may still brick your experiment, and without knowing about them you essentially have to shrug and trial and error your way through them. In contrast in a synthetic minimal cell, we could start out with an organism where we know 95% of the mechanisms that are going on, and then study new mechanisms one gene at a time, steadily building up to bigger and bigger mechanisms. Strangely it seems to me that a lot of effort is going more into being able to simulate full cells that contain unknown mechanisms, rather than trying to use the capabilities to create hypothesis to uncover the unknown mechanisms. Yes, that probably expedites the path towards simulating much bigger human cells, but ultimately still leaves us in the dark on most fronts.

suddenlybananas 1y ago
>Strangely it seems to me that a lot of effort is going more into being able to simulate full cells that contain unknown mechanisms, rather than trying to use the capabilities to create hypothesis to uncover the unknown mechanisms. Yes, that probably expedites the path towards simulating much bigger human cells, but ultimately still leaves us in the dark on most fronts. Seems the result of this general trend in science towards brute prediction and abandoning the goal of explanation or understanding.
- filoeleven 1y ago
  Check out Michael Levin’s lab for a refreshing and amazing example of a group that’s bucking the trend. They are doing tons of experiments by starting with the premise that cells and their networks have intelligence, then using tools from behavioral science to convince them to do what the experimenters want (e.g. “grow an eye here”). I’ve been convinced by Levin’s talks that this is a more promising area of research than genetics. https://drmichaellevin.org/ https://drmichaellevin.org/

moralestapia 1y ago

Great post. This is exactly what I'm an expert at, I even coined a term in the field [1], :). Since I started doing this 15 years ago (and I know the field predates me by much), one always has had this feeling that we are so close to a big breakthrough in biological simulation, but at the same time, progress has been kind of "slow". I think the reason for that is because pushing the envelope forward in this field requires mastering three (maybe four) different disciplines, your pick of [Bio, Chem, CS, Math, Physics]. Very few people reach this level of simultaneous understanding of all these pieces. I'm not trying to gatekeep the field, though, much of the progress here (including many of the papers mentioned in TFA) is work coming from PhD students. Anyone could jump into this, but you really need to sit down and try to make sense of it for a while, years. PhD gives one the perfect opportunity for that. Anyway, I hope this thing keeps going on forward, it's one of the ultimate goals of Biology and it would be extremely beneficial to the world. 1: https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2016.01881/full https://www.frontiersin.org/journals/plant-science/articles/...

_factor 1y ago
Thank you for your contributions. You are quite literally saving lives. Are there any good local (op-so ideally) tools and/or libraries one can experiment with? I have access to a couple HPC clusters and would love to learn more.
- moralestapia 1y ago
  Sure! Take a look at SimTK [1]. And I would try to reproduce Karr's model [2], paper here [3]; also mentioned in the linked page. This is the study that made me, and many others at the time, to actually take this seriously, lol. I was a student and was doing this as a hobby project, Karr's paper made me think "wait, this is actually possible, and today". It's really good if you want to learn and get your feet wet on this. If you want, you can reach out to me at hn @ moralestapia . com, and I'll be happy to recommend some more stuff! 1: https://simtk.org/ https://simtk.org/ 2: https://simtk.org/projects/wholecell https://simtk.org/projects/wholecell 3: https://www.cell.com/cell/fulltext/S0092-8674(12)00776-3 https://www.cell.com/cell/fulltext/S0092-8674(12)00776-3

maltee 1y ago

Great article! Also, really nice site design, the referenced papers and annotations are a really nice touch!