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Single-cell technologies now let us profile entire transcriptomes in individual cells. But how do we make sense of this complexity in a biologically meaningful way? Many methods summarise cells into a single embedding, but this often comes at the cost of interpretability, especially when multiple gene programs are active...

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Mo Lotfollahi

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22,440 views • 4 months ago •via X (Twitter)

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Excited to share our new work on building a multimodal atlas of human skin in health and inflammatory disease — a project I’m especially proud of, bringing together AI, high-throughput genomics, and clinical science to accelerate discovery. Over the past decade, single-cell genomics has transformed how we map cells in human tissues. But a major challenge remains: can we systematically decode how cells organize into functional niches in situ — including those invisible to standard histopathology? To address this, we integrated large-scale scRNA-seq, spatial transcriptomics, histopathology, and AI-driven modeling frameworks to build an in situ atlas of human skin across health and disease. Led by Lloyd Steele, an MD/PhD student working between Haniffa Lab and my lab at Wellcome Sanger Institute and Cambridge University . Another amazing collaboration with Muzz Haniffa, the mastermind behind the work as part of Human Cell Atlas. A key part of this study is that we didn’t build everything from scratch — we leveraged and combined AI methods that actually work! and showed how they can be used together to extract biological insight at scale. We used: • scArches to build and map into a reference scRNA-seq atlas of human skin: • NicheCompass to identify and characterize spatial niches: • MINT-Flow to extract microenvironment-induced cell states and gene programs: Together, these enabled an end-to-end workflow from atlas construction to spatial mapping, niche discovery, and cell state decoding. At scale, we integrated ~5 million cells and 100+ spatial sections, enabling a systematic view of tissue organization. Using this framework, we identified 26 niches in skin, including known histopathologic structures as well as hidden disease-associated niches not visible on H&E. Among the most striking findings were a resident memory T cell-rich sebaceous gland niche and a plasma cell-rich sweat gland niche, suggesting that appendageal structures act as active immunological microenvironments and may contribute to inflammatory memory and disease persistence. Importantly, this atlas is not just descriptive — it is usable. It can support mapping of new datasets, resolve finer cell types and niches, extract microenvironment-driven programs, and enable predictive analyses at scale. More broadly, this work shows what becomes possible when AI, spatial genomics, and atlas-scale data are integrated end-to-end: not just mapping tissues, but systematically decoding them. This was a massive collaboration, and I’m very grateful to the amazing scientists April Foster, Kenny Roberts, and Chloe Admane. Lloyd is an amazing scientist, and I’m especially excited for the community to see more of his work soon — stay tuned. The data and pre-trained models will be released soon. Preprint:
1:09

Excited to share our new work on building a multimodal atlas of human skin in health and inflammatory disease — a project I’m especially proud of, bringing together AI, high-throughput genomics, and clinical science to accelerate discovery. Over the past decade, single-cell genomics has transformed how we map cells in human tissues. But a major challenge remains: can we systematically decode how cells organize into functional niches in situ — including those invisible to standard histopathology? To address this, we integrated large-scale scRNA-seq, spatial transcriptomics, histopathology, and AI-driven modeling frameworks to build an in situ atlas of human skin across health and disease. Led by Lloyd Steele, an MD/PhD student working between Haniffa Lab and my lab at Wellcome Sanger Institute and Cambridge University . Another amazing collaboration with Muzz Haniffa, the mastermind behind the work as part of Human Cell Atlas. A key part of this study is that we didn’t build everything from scratch — we leveraged and combined AI methods that actually work! and showed how they can be used together to extract biological insight at scale. We used: • scArches to build and map into a reference scRNA-seq atlas of human skin: • NicheCompass to identify and characterize spatial niches: • MINT-Flow to extract microenvironment-induced cell states and gene programs: Together, these enabled an end-to-end workflow from atlas construction to spatial mapping, niche discovery, and cell state decoding. At scale, we integrated ~5 million cells and 100+ spatial sections, enabling a systematic view of tissue organization. Using this framework, we identified 26 niches in skin, including known histopathologic structures as well as hidden disease-associated niches not visible on H&E. Among the most striking findings were a resident memory T cell-rich sebaceous gland niche and a plasma cell-rich sweat gland niche, suggesting that appendageal structures act as active immunological microenvironments and may contribute to inflammatory memory and disease persistence. Importantly, this atlas is not just descriptive — it is usable. It can support mapping of new datasets, resolve finer cell types and niches, extract microenvironment-driven programs, and enable predictive analyses at scale. More broadly, this work shows what becomes possible when AI, spatial genomics, and atlas-scale data are integrated end-to-end: not just mapping tissues, but systematically decoding them. This was a massive collaboration, and I’m very grateful to the amazing scientists April Foster, Kenny Roberts, and Chloe Admane. Lloyd is an amazing scientist, and I’m especially excited for the community to see more of his work soon — stay tuned. The data and pre-trained models will be released soon. Preprint:

Mo Lotfollahi

11,759 views • 4 months ago

Excited to share our new work. Over the past decade, single-cell genomics has transformed our ability to map cellular systems. But a major question remains: Can we predict how perturbations reshape cellular trajectories over time? In 2018, we first showed that it is possible to predict cellular responses to perturbations — ranging from disease signals to chemical treatments — even in unseen contexts. In 2022, we introduced CPA (MSB 2022; NeurIPS 2022), extending this idea to predict responses to unseen chemical and genetic perturbations, including their combinations. Since then, the field of perturbation modeling has grown enormously. The community has pushed the space forward with many creative ideas and powerful models. It’s exciting to see how fast things are moving — even though many fundamental challenges remain. One of the biggest is that cells are not static. They move through trajectories during development, immune responses, and disease. Yet most current models still predict perturbation effects within a single state, rather than how early perturbations propagate across future states and reshape downstream outcomes. To address this, we developed PerturbGen, a trajectory-aware generative AI model that predicts how genetic perturbations reshape downstream cellular states. Huge credit to the people who made this work possible. Thanks to co-first authors Kevin Ly, Adib Miraki, Tomoya Isobe, AmirHoss3in Vahidi, Delshad Vaghari & Anthony Rostron. Special recognition to Kevin Ly and Adib Miraki for driving this work over the finish line. Grateful for our outstanding collaborators from Haniffa Lab, Bertie Gottgens lab Gosia Trynka and many others — a true cross-institute effort across Cambridge Stem Cell Institute, Open Targets ,Wellcome Sanger Institute and Cambridge University.🎉 PerturbGen learns transcriptional dynamics across cellular trajectories. By introducing perturbations at an early source state, it can simulate how these effects propagate into future states along differentiation trajectories. Scaling this across genes enables the creation of dynamic in silico perturbation atlases — maps of how perturbations reshape biological trajectories over time. We explored this idea across three biological questions. First, in a human in vivo LPS immune challenge, PerturbGen predicted that perturbing a transient IL1B signal dampens downstream inflammatory programs in myeloid cells, with pathway changes reversing signatures observed in an independent IL-1β stimulation experiment. Second, in human hematopoiesis, PerturbGen predicted transcriptional responses to CRISPR transcription factor knockouts and enabled construction of perturbation atlases revealing lineage- and age-specific regulatory programs. These programs could also be linked to human genetics and blood diseases, including recapitulation of signatures associated with ETV6-related thrombocytopenia. Finally, we asked whether perturbation modeling could help improve complex tissue models. We built a dynamic perturbation atlas of human skin organoids to identify perturbations that could guideorganoid cells towardhuman fetal skin states. PerturbGen prioritized activation of Wnt signaling via GSK3β inhibition. Experimental validation confirmed the prediction: treatment with CHIR99021 induced stromal gene programs and shifted organoid fibroblasts toward transcriptional states observed in fetal skin stroma. Together, these results show how trajectory-aware perturbation modeling can connect gene perturbations to developmental programs, human genetics, disease mechanisms, and experimental interventions. More broadly, we think these point toward a future where single-cell atlases become predictive systems. As atlases expand across tissues, developmental windows, and modalities, models like PerturbGen could enable dynamic, virtual perturbation atlases— allowing us to simulate interventions, generate hypotheses, and design experiments before stepping into the lab. Preprint Code Excited to see how the community builds on this work.
2:46

Excited to share our new work. Over the past decade, single-cell genomics has transformed our ability to map cellular systems. But a major question remains: Can we predict how perturbations reshape cellular trajectories over time? In 2018, we first showed that it is possible to predict cellular responses to perturbations — ranging from disease signals to chemical treatments — even in unseen contexts. In 2022, we introduced CPA (MSB 2022; NeurIPS 2022), extending this idea to predict responses to unseen chemical and genetic perturbations, including their combinations. Since then, the field of perturbation modeling has grown enormously. The community has pushed the space forward with many creative ideas and powerful models. It’s exciting to see how fast things are moving — even though many fundamental challenges remain. One of the biggest is that cells are not static. They move through trajectories during development, immune responses, and disease. Yet most current models still predict perturbation effects within a single state, rather than how early perturbations propagate across future states and reshape downstream outcomes. To address this, we developed PerturbGen, a trajectory-aware generative AI model that predicts how genetic perturbations reshape downstream cellular states. Huge credit to the people who made this work possible. Thanks to co-first authors Kevin Ly, Adib Miraki, Tomoya Isobe, AmirHoss3in Vahidi, Delshad Vaghari & Anthony Rostron. Special recognition to Kevin Ly and Adib Miraki for driving this work over the finish line. Grateful for our outstanding collaborators from Haniffa Lab, Bertie Gottgens lab Gosia Trynka and many others — a true cross-institute effort across Cambridge Stem Cell Institute, Open Targets ,Wellcome Sanger Institute and Cambridge University.🎉 PerturbGen learns transcriptional dynamics across cellular trajectories. By introducing perturbations at an early source state, it can simulate how these effects propagate into future states along differentiation trajectories. Scaling this across genes enables the creation of dynamic in silico perturbation atlases — maps of how perturbations reshape biological trajectories over time. We explored this idea across three biological questions. First, in a human in vivo LPS immune challenge, PerturbGen predicted that perturbing a transient IL1B signal dampens downstream inflammatory programs in myeloid cells, with pathway changes reversing signatures observed in an independent IL-1β stimulation experiment. Second, in human hematopoiesis, PerturbGen predicted transcriptional responses to CRISPR transcription factor knockouts and enabled construction of perturbation atlases revealing lineage- and age-specific regulatory programs. These programs could also be linked to human genetics and blood diseases, including recapitulation of signatures associated with ETV6-related thrombocytopenia. Finally, we asked whether perturbation modeling could help improve complex tissue models. We built a dynamic perturbation atlas of human skin organoids to identify perturbations that could guideorganoid cells towardhuman fetal skin states. PerturbGen prioritized activation of Wnt signaling via GSK3β inhibition. Experimental validation confirmed the prediction: treatment with CHIR99021 induced stromal gene programs and shifted organoid fibroblasts toward transcriptional states observed in fetal skin stroma. Together, these results show how trajectory-aware perturbation modeling can connect gene perturbations to developmental programs, human genetics, disease mechanisms, and experimental interventions. More broadly, we think these point toward a future where single-cell atlases become predictive systems. As atlases expand across tissues, developmental windows, and modalities, models like PerturbGen could enable dynamic, virtual perturbation atlases— allowing us to simulate interventions, generate hypotheses, and design experiments before stepping into the lab. Preprint Code Excited to see how the community builds on this work.

Mo Lotfollahi

17,035 views • 4 months ago

Scientists just figured out how to reverse aging using AI. And this is a massive breakthrough. We can now reprogram any human cell back to age 20. Heart cells, brain cells, skin cells, all reset to their biological prime. And here’s the wildest part…the technology to do this, has already existed since 2012 (it won the Nobel Prize). But the real breakthrough wasn’t possible until this year, when they supercharged it with AI. It’s a wild story. So in 2006, scientists discovered Yamanaka factors. They’re proteins that can basically convert any normal cell into a universal stem cell. Now this was a huge deal, because these stem cells are basically like magic healers. If you have torn muscle tissue, you could inject these stem cells into the area and they will turn into the youthful muscle cells you need. So Yamanaka factors were this insane breakthrough, because they allowed any human to turn any cell you already have into these magic healers. But, there was one big problem… It turns out, the original Yamanaka factors weren’t very good at this stem cell conversion. They could do it, but they just weren’t very reliable. Enter OpenAI...and this is where things get crazy. OpenAI designed a special AI model built specifically to create new proteins. Think of it like ChatGPT but for protein engineering. So they took all the Yamanaka research and asked this new AI to go ham on improving it. And get this… Their version was 50x more effective than the original. They tested it on 50 year old cells and it successfully started repairing 30% of their cells in just 7 days. This is just science fiction…it actually happened. And it sounds crazy, but in a few years, humans will be able to take a shot that will literally reverse the age of their cells.
1:32

Scientists just figured out how to reverse aging using AI. And this is a massive breakthrough. We can now reprogram any human cell back to age 20. Heart cells, brain cells, skin cells, all reset to their biological prime. And here’s the wildest part…the technology to do this, has already existed since 2012 (it won the Nobel Prize). But the real breakthrough wasn’t possible until this year, when they supercharged it with AI. It’s a wild story. So in 2006, scientists discovered Yamanaka factors. They’re proteins that can basically convert any normal cell into a universal stem cell. Now this was a huge deal, because these stem cells are basically like magic healers. If you have torn muscle tissue, you could inject these stem cells into the area and they will turn into the youthful muscle cells you need. So Yamanaka factors were this insane breakthrough, because they allowed any human to turn any cell you already have into these magic healers. But, there was one big problem… It turns out, the original Yamanaka factors weren’t very good at this stem cell conversion. They could do it, but they just weren’t very reliable. Enter OpenAI...and this is where things get crazy. OpenAI designed a special AI model built specifically to create new proteins. Think of it like ChatGPT but for protein engineering. So they took all the Yamanaka research and asked this new AI to go ham on improving it. And get this… Their version was 50x more effective than the original. They tested it on 50 year old cells and it successfully started repairing 30% of their cells in just 7 days. This is just science fiction…it actually happened. And it sounds crazy, but in a few years, humans will be able to take a shot that will literally reverse the age of their cells.

Whiplash347

68,643 views • 8 months ago

How does an embryo reliably "compute" its form - "cell by cell" - using only local interactions and mechanics, yet produce a precise global body plan? I’m excited to share our Nature Methods paper "MultiCell: geometric learning in multicellular development", presenting #AIxBiology research led by Haiqian Yang and the result of a great collaboration with Ming Guo, George Roy, Tomer Stern, Anh Nguyen and Dapeng Bi. A long-standing challenge in developmental biology is to predict how thousands of cells collectively self-organize as tissues fold, divide, and rearrange. In MultiCell, we represent a developing embryo as a dual graph that unifies two complementary views of tissue mechanics with single-cell resolution: cells as moving points (granular) and cells as a connected foam (junction network). This lets the model learn dynamics from both geometry and cell–cell connectivity. On whole-embryo 4D light-sheet movies of Drosophila gastrulation (~5,000 cells), our model predicts key cell behaviors and the timing of events, including junction loss, rearrangements, and divisions with high accuracy, at single-cell resolution. Beyond prediction, the same representation supports robust time alignment across embryos and offers interpretable activation maps that highlight the morphogenetic "drivers" of development. The broader goal is a foundation for cell-by-cell forecasting in more complex tissues, and eventually for detecting subtle dynamical signatures of disease. Kudos to the team for this inspiring collaboration with brilliant researchers to push the boundary of AI for biology! Citation: Yang, H., Roy, G., Nguyen, A.Q., Buehler, M.J., et al. MultiCell: geometric learning in multicellular development. Nature Methods (2025), DOI: 10.1038/s41592-025-02983-x Code/data links are in the manuscript.
0:46

How does an embryo reliably "compute" its form - "cell by cell" - using only local interactions and mechanics, yet produce a precise global body plan? I’m excited to share our Nature Methods paper "MultiCell: geometric learning in multicellular development", presenting #AIxBiology research led by Haiqian Yang and the result of a great collaboration with Ming Guo, George Roy, Tomer Stern, Anh Nguyen and Dapeng Bi. A long-standing challenge in developmental biology is to predict how thousands of cells collectively self-organize as tissues fold, divide, and rearrange. In MultiCell, we represent a developing embryo as a dual graph that unifies two complementary views of tissue mechanics with single-cell resolution: cells as moving points (granular) and cells as a connected foam (junction network). This lets the model learn dynamics from both geometry and cell–cell connectivity. On whole-embryo 4D light-sheet movies of Drosophila gastrulation (~5,000 cells), our model predicts key cell behaviors and the timing of events, including junction loss, rearrangements, and divisions with high accuracy, at single-cell resolution. Beyond prediction, the same representation supports robust time alignment across embryos and offers interpretable activation maps that highlight the morphogenetic "drivers" of development. The broader goal is a foundation for cell-by-cell forecasting in more complex tissues, and eventually for detecting subtle dynamical signatures of disease. Kudos to the team for this inspiring collaboration with brilliant researchers to push the boundary of AI for biology! Citation: Yang, H., Roy, G., Nguyen, A.Q., Buehler, M.J., et al. MultiCell: geometric learning in multicellular development. Nature Methods (2025), DOI: 10.1038/s41592-025-02983-x Code/data links are in the manuscript.

Markus J. Buehler

387,977 views • 7 months ago

We are thrilled to share that our first paper from my new lab, Spateo ( for spatiotemporal modeling of molecular holograms, is now online in Cell: Spateo is a comprehensive analytical framework for 3D whole-embryo spatiotemporal modeling. Its advanced features include: • 3D alignment and reconstruction at the whole-mouse-embryo scale (see the animation). • 3D spatial domain digitization and cell-cell communication analysis to understand spatial gene expression gradients and both inter- and intracellular communication. • 3D morphometric and volumetric analyses along with 3D morphogenesis vector field modeling to quantify dynamics such as surface area, volume, and cell density across organs, and to dissect the interplay between morphogenesis factors and cell migration. • A “Google Earth”-like browser, Spateo-viewer ( and for interactive and intuitive exploration of 3D spatial data. • Additional features, such as RNA signal-based single-cell segmentation. We are also honored that Nature “News and Views” has highlighted this work as well: This is really an amazing outcome after two years' heroic revision process that rewrite the entire paper using a new data ( for whole mouse embryos.
1:24

We are thrilled to share that our first paper from my new lab, Spateo ( for spatiotemporal modeling of molecular holograms, is now online in Cell: Spateo is a comprehensive analytical framework for 3D whole-embryo spatiotemporal modeling. Its advanced features include: • 3D alignment and reconstruction at the whole-mouse-embryo scale (see the animation). • 3D spatial domain digitization and cell-cell communication analysis to understand spatial gene expression gradients and both inter- and intracellular communication. • 3D morphometric and volumetric analyses along with 3D morphogenesis vector field modeling to quantify dynamics such as surface area, volume, and cell density across organs, and to dissect the interplay between morphogenesis factors and cell migration. • A “Google Earth”-like browser, Spateo-viewer ( and for interactive and intuitive exploration of 3D spatial data. • Additional features, such as RNA signal-based single-cell segmentation. We are also honored that Nature “News and Views” has highlighted this work as well: This is really an amazing outcome after two years' heroic revision process that rewrite the entire paper using a new data ( for whole mouse embryos.

evo-devo

58,343 views • 1 year ago

RFK Jr. says he is working with insurance companies to start covering treatment that can cure sickle cell. “I spent the day with a young woman who was in agony because of sickle cell… and she now has a full life because she received this treatment.” “If we can give that to people that’s almost providential power.” “I was in South Carolina inking the final documents on a deal that we've put together… to make this particular cell and gene therapy available to every person in the state who has sickle cell with it being fully paid for.” “We're negotiating now with 38 other states and by the end of next year we hope to have this available to every American.” “It's saving the insurance companies money… if they look at the total cost over the lifetime of that child it's an enormous saving because even though it's a very expensive drug, it's a one time treatment.”
2:13

RFK Jr. says he is working with insurance companies to start covering treatment that can cure sickle cell. “I spent the day with a young woman who was in agony because of sickle cell… and she now has a full life because she received this treatment.” “If we can give that to people that’s almost providential power.” “I was in South Carolina inking the final documents on a deal that we've put together… to make this particular cell and gene therapy available to every person in the state who has sickle cell with it being fully paid for.” “We're negotiating now with 38 other states and by the end of next year we hope to have this available to every American.” “It's saving the insurance companies money… if they look at the total cost over the lifetime of that child it's an enormous saving because even though it's a very expensive drug, it's a one time treatment.”

End Tribalism in Politics

35,435 views • 1 year ago

🚨🚨🚨 Dutch Cancer Researcher and Erasmus Medical Centre Assc Prof Maarten Fornerod discusses DNA contamination in COVID Vaccines. ---------------------------- ...for last 35 years or so I've been working uh in the areas of molecular biology, gene expression, biology, cancer biology and recently in the last years, maybe last 10 years in the context of big data and computational biology... ...when we use genetic vaccines what we do essentially is we're making a complex intervention in a very complex system. It's impossible to predict what happens if you combine these two complex systems, and you get unpredictable effects. .. And the only way to go about this is to do genotoxic research, when you want to introduce a genetic medicine into a human being and that genetotic research has to be independent, it has to be double blind, has to be long lasting. AND ALL THESE HAVE NOT BEEN DONE WITH THE GENETIC CORONA VACCINES! if there's a vaccine, there's a little bit of DNA in there upon injection that is very, very rapidly degraded by the human body. However if it's protected and in a lipid nanoarticle it can very efficiently be transduced in the cell... I've been doing this this many, many times. This is called lipofection and it's a very efficient way to introduce DNA into a cell. ...Many people think that this is not possible. But I've been working in nuclear transport for many years, I think more than 10 years. So I've been exposed to a lot of molecular cell biology of nuclear cytoplasmic transport. And it's clear that the DNA can enter the nucleus. Now to make things worse, the mRNA vaccine doesn't stay in the arm but it's detected in , in all different organs including the reproductive system. And so partly this is based on animal models, of course we know from Michael Morz that he has detected uh the spike protein in brain, in the heart and it's for sure it's detected in the blood and even in breast milk. ..So there's NO DOUBT that this mRNA vaccine spreads widely in the human body. ..Now from a genetic point of view, there are possible consequences uh of this and the consequences could be a 1. long term disruption of cellular processes that could lead to disease. 2. there's a risk of insertional mutageenesis in somatic cells that can lead to cancer. 3. the insertion mutogenesis takes place in a germ cell which would be a hereditary burden uh on the human population. 4. And you could also think that these um DNAs, could transfect the microbiome and it could possibly lead to bacterial resistance. So these are all possible..the consequences of these genetic vaccines in my view, the shortcomings in this rollout of these vaccines were there was no genotoxic research performed at all. There was no safety studies, on carcinogenic potential of these vaccines. My personal opinion is that it's now not a question of whether, it will integrate in recipient's DNA, but how often it occurs... It's just a numbers game. If you do this in many cells, many persons it will no doubt integrate in cells in human recipients. So the question does it affect the human genome? I would say it probably, I think it most certainly does. And you see Kevin McKernan here and he represented ah a preliminary data where he detected a possible Pfizer DNA in colon cancer biopsy one year after vaccination.
6:25

🚨🚨🚨 Dutch Cancer Researcher and Erasmus Medical Centre Assc Prof Maarten Fornerod discusses DNA contamination in COVID Vaccines. ---------------------------- ...for last 35 years or so I've been working uh in the areas of molecular biology, gene expression, biology, cancer biology and recently in the last years, maybe last 10 years in the context of big data and computational biology... ...when we use genetic vaccines what we do essentially is we're making a complex intervention in a very complex system. It's impossible to predict what happens if you combine these two complex systems, and you get unpredictable effects. .. And the only way to go about this is to do genotoxic research, when you want to introduce a genetic medicine into a human being and that genetotic research has to be independent, it has to be double blind, has to be long lasting. AND ALL THESE HAVE NOT BEEN DONE WITH THE GENETIC CORONA VACCINES! if there's a vaccine, there's a little bit of DNA in there upon injection that is very, very rapidly degraded by the human body. However if it's protected and in a lipid nanoarticle it can very efficiently be transduced in the cell... I've been doing this this many, many times. This is called lipofection and it's a very efficient way to introduce DNA into a cell. ...Many people think that this is not possible. But I've been working in nuclear transport for many years, I think more than 10 years. So I've been exposed to a lot of molecular cell biology of nuclear cytoplasmic transport. And it's clear that the DNA can enter the nucleus. Now to make things worse, the mRNA vaccine doesn't stay in the arm but it's detected in , in all different organs including the reproductive system. And so partly this is based on animal models, of course we know from Michael Morz that he has detected uh the spike protein in brain, in the heart and it's for sure it's detected in the blood and even in breast milk. ..So there's NO DOUBT that this mRNA vaccine spreads widely in the human body. ..Now from a genetic point of view, there are possible consequences uh of this and the consequences could be a 1. long term disruption of cellular processes that could lead to disease. 2. there's a risk of insertional mutageenesis in somatic cells that can lead to cancer. 3. the insertion mutogenesis takes place in a germ cell which would be a hereditary burden uh on the human population. 4. And you could also think that these um DNAs, could transfect the microbiome and it could possibly lead to bacterial resistance. So these are all possible..the consequences of these genetic vaccines in my view, the shortcomings in this rollout of these vaccines were there was no genotoxic research performed at all. There was no safety studies, on carcinogenic potential of these vaccines. My personal opinion is that it's now not a question of whether, it will integrate in recipient's DNA, but how often it occurs... It's just a numbers game. If you do this in many cells, many persons it will no doubt integrate in cells in human recipients. So the question does it affect the human genome? I would say it probably, I think it most certainly does. And you see Kevin McKernan here and he represented ah a preliminary data where he detected a possible Pfizer DNA in colon cancer biopsy one year after vaccination.

aussie17

126,273 views • 1 year ago

This is crazy! This is some of the complex systems working inside your cells. God's Design inside every single cell in your body. Cells cannot arise through evolution. The minimum viable cell requires: - Around ~500,000 lines of coded information (DNA) - Close to ~500 unique protein products (the building blocks of all those cellular machines and systems) - Total of ~20k-50k total proteins all working perfectly together - Around ~30-40 regulatory systems guiding all those interactions The cell requires all those parts & systems, or it doesn't function. If we do the math, there are about ~10^70,000 possible interactions in this cell. Interactions are things like: - energy production - waste removal - protein creation - system repair The odds are incomprehensible. Evolutionists will argue the odds are misleading, because it evolves gradually via step-by-step trial & error. But the cell REQUIRES a minimum set of parts & systems to function - without all of these in place, together, from the beginning, it dies. Therefore, the cell cannot evolve through step-by-step evolutionary processes, because there is no reproduction + mutation to drive evolutionary change until the cell is complete. Cells are a massive problem for Evolutionism, because they are such obvious signs of Intelligent Design. Even the famous atheist Richard Dawkins admitted that, "Biology is the study of complicated things that have the appearance of having been designed with a purpose." Biology seems designed because it IS designed. God's Divine Design becomes more obvious, the closer we look.
1:28

This is crazy! This is some of the complex systems working inside your cells. God's Design inside every single cell in your body. Cells cannot arise through evolution. The minimum viable cell requires: - Around ~500,000 lines of coded information (DNA) - Close to ~500 unique protein products (the building blocks of all those cellular machines and systems) - Total of ~20k-50k total proteins all working perfectly together - Around ~30-40 regulatory systems guiding all those interactions The cell requires all those parts & systems, or it doesn't function. If we do the math, there are about ~10^70,000 possible interactions in this cell. Interactions are things like: - energy production - waste removal - protein creation - system repair The odds are incomprehensible. Evolutionists will argue the odds are misleading, because it evolves gradually via step-by-step trial & error. But the cell REQUIRES a minimum set of parts & systems to function - without all of these in place, together, from the beginning, it dies. Therefore, the cell cannot evolve through step-by-step evolutionary processes, because there is no reproduction + mutation to drive evolutionary change until the cell is complete. Cells are a massive problem for Evolutionism, because they are such obvious signs of Intelligent Design. Even the famous atheist Richard Dawkins admitted that, "Biology is the study of complicated things that have the appearance of having been designed with a purpose." Biology seems designed because it IS designed. God's Divine Design becomes more obvious, the closer we look.

Divinely Designed

32,233 views • 4 months ago

Science Corner: David Friedberg Explains Recent Mitotherapy Breakthroughs ⚡️ On E224, david friedberg broke down what mitotherapy is and how recent discoveries could unleash this treatment for many diseases: "So mitochondria are the powerhouse of the cell." "Every cell in our body gets its energy, which is what it uses to function, from the mitochondria." "And so there's been a lot of research into the relationship between mitochondria and aging, and that dysfunctional mitochondria may actually be a key driver for many diseases." "Including many cancers, Alzheimer's, Parkinson's, ALS, features of autism, muscle tissues being weak, etc." " So, as the cells get older and the mitochondria stop working, we make new mitochondria." "But over time, the DNA degrades and the mitochondria become less effective and there are fewer functional mitochondria per cell." Friedberg highlighted three recent papers: 1) "The power and potential of mitochondria transfer" (nature) -- "these folks identified and demonstrated that mitochondria can actually transfer from one cell to another" -- " So, if you've got a cell that's got damaged, or dysfunctional mitochondria, they've identified three mechanisms by which mitochondria can move into a cell that needs more mitochondria that are working and are more functional." -- "And as a result, it can rejuvenate or provide energy to a dysfunctional cell, which might improve dysfunctional tissue or improve disease." 2) "A human brain map of mitochondrial respiratory capacity and diversity" (nature) -- " this was the first mapping of the mitochondria in the human brain" -- " what it showed was that different parts of the brain, different cells, had different amounts of mitochondria and different mitochondrial function." -- "(This) starts to highlight how that difference in energy production in different cells in different parts of the brain may actually cause some of the things like memory loss or speech impairment," -- "the mitochondrial dysfunction in the brain might actually be the key driver of that aging symptomology." 3) "Organelle-tuning condition robustly fabricates energetic mitochondria for cartilage regeneration" (nature | Bone Research) -- " (the researchers) figured out a way to treat stem cells so that (they) would start to make an excess amount of mitochondria than they normally would make" -- " So they created highly energetic mitochondria and they made a lot of them." -- " the idea that we can put mitochondria into our body or into tissue in our body to heal it or repair it has been something that folks have been trying to do research around for a long time" -- " but the limiting factor is access to enough mitochondria" -- " so this mechanism that they developed opens up the door to this whole new therapeutic modality, a new type of therapy called mitotherapy" Conclusion: " ... based on the series of papers that we're seeing coming out recently, I believe (this) could end up becoming a really incredible new therapy that may ultimately lead to the treatment for many diseases that we're dealing with right now."
2:46

Science Corner: David Friedberg Explains Recent Mitotherapy Breakthroughs ⚡️ On E224, david friedberg broke down what mitotherapy is and how recent discoveries could unleash this treatment for many diseases: "So mitochondria are the powerhouse of the cell." "Every cell in our body gets its energy, which is what it uses to function, from the mitochondria." "And so there's been a lot of research into the relationship between mitochondria and aging, and that dysfunctional mitochondria may actually be a key driver for many diseases." "Including many cancers, Alzheimer's, Parkinson's, ALS, features of autism, muscle tissues being weak, etc." " So, as the cells get older and the mitochondria stop working, we make new mitochondria." "But over time, the DNA degrades and the mitochondria become less effective and there are fewer functional mitochondria per cell." Friedberg highlighted three recent papers: 1) "The power and potential of mitochondria transfer" (nature) -- "these folks identified and demonstrated that mitochondria can actually transfer from one cell to another" -- " So, if you've got a cell that's got damaged, or dysfunctional mitochondria, they've identified three mechanisms by which mitochondria can move into a cell that needs more mitochondria that are working and are more functional." -- "And as a result, it can rejuvenate or provide energy to a dysfunctional cell, which might improve dysfunctional tissue or improve disease." 2) "A human brain map of mitochondrial respiratory capacity and diversity" (nature) -- " this was the first mapping of the mitochondria in the human brain" -- " what it showed was that different parts of the brain, different cells, had different amounts of mitochondria and different mitochondrial function." -- "(This) starts to highlight how that difference in energy production in different cells in different parts of the brain may actually cause some of the things like memory loss or speech impairment," -- "the mitochondrial dysfunction in the brain might actually be the key driver of that aging symptomology." 3) "Organelle-tuning condition robustly fabricates energetic mitochondria for cartilage regeneration" (nature | Bone Research) -- " (the researchers) figured out a way to treat stem cells so that (they) would start to make an excess amount of mitochondria than they normally would make" -- " So they created highly energetic mitochondria and they made a lot of them." -- " the idea that we can put mitochondria into our body or into tissue in our body to heal it or repair it has been something that folks have been trying to do research around for a long time" -- " but the limiting factor is access to enough mitochondria" -- " so this mechanism that they developed opens up the door to this whole new therapeutic modality, a new type of therapy called mitotherapy" Conclusion: " ... based on the series of papers that we're seeing coming out recently, I believe (this) could end up becoming a really incredible new therapy that may ultimately lead to the treatment for many diseases that we're dealing with right now."

The All-In Podcast

58,412 views • 1 year ago

Ok so treatment has begun here at Auragens. First day I’m getting stem cells via IV, these cells are from an umbilical chord, so basically Day One cells that haven’t been programmed yet, is how it was explained to me and the wild thing is the cells know where to go in your body to attack inflammation and injuries. Wifey getting stem cell facials and IVs for anti-aging. I am also having exosomes in a nebulizer for brain health. GOD knows I need all the help I can get with that. During this trip I will have a tuneup in my left shoulder, which needs a MAJOR surgery and I treated with stem cells right before season for pain management to get me through season until i have time for surgery this offseason Also I’m doing a veryyy cutting edge procedure this time where i will go under anesthesia and they will inject stem cells directly into my discs. I’ve have multiple, multiple, multiple ruptures and herniations over the years from training NFL players and fighters in MMA. Couple years ago was supposed to get either a three-level fusion or a rod inserted into my back. That would have changed my life forever and something I’m not prepared for. But right before my scheduled fusion, I threw up a Hail Mary, came down here for stem cell treatment, got the cells and i couldn’t believe it but shortly after treatment I was actually pain-free! I couldn’t believe it. I went to NFL training camp shortly after and people around the league actually noticed a difference in how i was standing and moving and not constantly trying to stretch and do things I used to do for pain relief. Shortly after I actually CANCELLED my surgery!!! My MRI is still completely disgusting so may need a surgery in future but I’ve bought 2 years without a surgery as a result of these stem cells and hoping this procedure I’m doing down here this time gives me many many more years. I’m hopeful. Hope is a great thing to have. Will keep ya updated how it’s going. If you want info on this DM Percy Knox Jr not me! lol. He knows more about it than I do! Btw going from here and beauty of Panama right to #nflcombine where it starts up allll over again. NFL never ends #stemcell #therapy #backpain #stemcelltreatment #panama #panamacity
1:01

Ok so treatment has begun here at Auragens. First day I’m getting stem cells via IV, these cells are from an umbilical chord, so basically Day One cells that haven’t been programmed yet, is how it was explained to me and the wild thing is the cells know where to go in your body to attack inflammation and injuries. Wifey getting stem cell facials and IVs for anti-aging. I am also having exosomes in a nebulizer for brain health. GOD knows I need all the help I can get with that. During this trip I will have a tuneup in my left shoulder, which needs a MAJOR surgery and I treated with stem cells right before season for pain management to get me through season until i have time for surgery this offseason Also I’m doing a veryyy cutting edge procedure this time where i will go under anesthesia and they will inject stem cells directly into my discs. I’ve have multiple, multiple, multiple ruptures and herniations over the years from training NFL players and fighters in MMA. Couple years ago was supposed to get either a three-level fusion or a rod inserted into my back. That would have changed my life forever and something I’m not prepared for. But right before my scheduled fusion, I threw up a Hail Mary, came down here for stem cell treatment, got the cells and i couldn’t believe it but shortly after treatment I was actually pain-free! I couldn’t believe it. I went to NFL training camp shortly after and people around the league actually noticed a difference in how i was standing and moving and not constantly trying to stretch and do things I used to do for pain relief. Shortly after I actually CANCELLED my surgery!!! My MRI is still completely disgusting so may need a surgery in future but I’ve bought 2 years without a surgery as a result of these stem cells and hoping this procedure I’m doing down here this time gives me many many more years. I’m hopeful. Hope is a great thing to have. Will keep ya updated how it’s going. If you want info on this DM Percy Knox Jr not me! lol. He knows more about it than I do! Btw going from here and beauty of Panama right to #nflcombine where it starts up allll over again. NFL never ends #stemcell #therapy #backpain #stemcelltreatment #panama #panamacity

Jay Glazer

252,987 views • 1 year ago

Dr. Patrick Soon-Shiong on the Cancer-Fighting Immune Breakthrough: Awakening the 450 Million-Year-Old Natural Killer Cell After decades of pioneering work since discovering the natural killer cell in the 1990s—a remarkable immune cell created by God and preserved through 450 million years—Dr. Patrick Soon-Shiong reveals an extraordinary breakthrough. This cell, unknown to many until the 1970s, serves as the body's first line of defense, designed to destroy cancer cells, infections like COVID, sepsis, bacteria, and fungus. Dr. Soon-Shiong emphasizes that this is not an invention, but an enlightenment: activating the body’s own natural killer cells to combat disease naturally, shifting away from toxic chemotherapy and radiation. With a single jab, they have unlocked the secret to empowering this primal cellular protector. This is evolution’s own weapon against illness, a game-changer that taps into ancient biology to revolutionize modern medicine. This insight reframes how we think about health and cancer treatment by harnessing the immune system's innate power, moving beyond harsh treatments, and embracing nature’s original disease-fighter from within. The discovery is a call to awaken the body’s own god-given defense system for a future of empowered healing.
1:58

Dr. Patrick Soon-Shiong on the Cancer-Fighting Immune Breakthrough: Awakening the 450 Million-Year-Old Natural Killer Cell After decades of pioneering work since discovering the natural killer cell in the 1990s—a remarkable immune cell created by God and preserved through 450 million years—Dr. Patrick Soon-Shiong reveals an extraordinary breakthrough. This cell, unknown to many until the 1970s, serves as the body's first line of defense, designed to destroy cancer cells, infections like COVID, sepsis, bacteria, and fungus. Dr. Soon-Shiong emphasizes that this is not an invention, but an enlightenment: activating the body’s own natural killer cells to combat disease naturally, shifting away from toxic chemotherapy and radiation. With a single jab, they have unlocked the secret to empowering this primal cellular protector. This is evolution’s own weapon against illness, a game-changer that taps into ancient biology to revolutionize modern medicine. This insight reframes how we think about health and cancer treatment by harnessing the immune system's innate power, moving beyond harsh treatments, and embracing nature’s original disease-fighter from within. The discovery is a call to awaken the body’s own god-given defense system for a future of empowered healing.

Camus

33,407 views • 8 months ago

"The real dangerous thing about the Pfizer DNA". "It's like one of these self-amplifying RNA's". Genomics expert Kevin McKernan has seen DNA contamination 10- to 100-fold above safety limits and they haven't even tested the "E Lots" containing the super dangerous vials. "[In] a study from Professor Ulrike Kämmerer in Germany [she] transfected cell lines with the vaccine in petri dishes [and] she watched those through several cell divisions, and the SV40 was staying with them throughout the cell divisions." Transcript, Kevin McKernan: "That's the really dangerous thing about the Pfizer DNA. Unlike the Moderna DNA, they left a mammalian origin of replication in there. So, if it gets into a mammalian cell, it's capable of making more copies of itself once it's in there. In essence, it's like one of these self-amplifying RNAs that everyone's ludicrously thinking about releasing right now. There has been a study from Professor Ulrike Kämmerer in Germany where she transfected cell lines with the vaccine in petri dishes. Not the virus—I'm sorry, the vaccine. I might as well call it a virus at this stage, and she watched those through several cell divisions, and the SV40 was staying with them throughout the cell divisions. That's a sign that it is replication-competent to some degree. That's still yet to be done with the really egregious lots—the E lots. I bet if we did those, there would be full-length plasmids in those, and they would stay permanently in those cell lines. But we don't have access to those. For those not familiar with these E lots, there's a Schmeling et al. paper that showed that about four percent of the lots are responsible for about 77% of the adverse events. None of those have been surveyed yet for this. We're finding contamination 10- to 100-fold above the limit in the lots that had low adverse events. Wait until we get to the ones that are really hurting people."
1:24

"The real dangerous thing about the Pfizer DNA". "It's like one of these self-amplifying RNA's". Genomics expert Kevin McKernan has seen DNA contamination 10- to 100-fold above safety limits and they haven't even tested the "E Lots" containing the super dangerous vials. "[In] a study from Professor Ulrike Kämmerer in Germany [she] transfected cell lines with the vaccine in petri dishes [and] she watched those through several cell divisions, and the SV40 was staying with them throughout the cell divisions." Transcript, Kevin McKernan: "That's the really dangerous thing about the Pfizer DNA. Unlike the Moderna DNA, they left a mammalian origin of replication in there. So, if it gets into a mammalian cell, it's capable of making more copies of itself once it's in there. In essence, it's like one of these self-amplifying RNAs that everyone's ludicrously thinking about releasing right now. There has been a study from Professor Ulrike Kämmerer in Germany where she transfected cell lines with the vaccine in petri dishes. Not the virus—I'm sorry, the vaccine. I might as well call it a virus at this stage, and she watched those through several cell divisions, and the SV40 was staying with them throughout the cell divisions. That's a sign that it is replication-competent to some degree. That's still yet to be done with the really egregious lots—the E lots. I bet if we did those, there would be full-length plasmids in those, and they would stay permanently in those cell lines. But we don't have access to those. For those not familiar with these E lots, there's a Schmeling et al. paper that showed that about four percent of the lots are responsible for about 77% of the adverse events. None of those have been surveyed yet for this. We're finding contamination 10- to 100-fold above the limit in the lots that had low adverse events. Wait until we get to the ones that are really hurting people."

Humanspective

15,938 views • 1 year ago

This is how DNA is organized in a cell. And it's more evidence that Life was intelligently designed. Each human cell contains about 6.5ft (2m) of DNA packed into a dense microscopic structure. But it's not packed into a random pile. It's packed into precise loops scientists call 'cohesin loops.' DNA is wound up around spool-like proteins called histones, which are then further wound together into clusters called nucleosomes, which are then organized into shapes called chromatins, which are then folded into large structures called chromosomes. Four levels of very specific, complex organization. Without a specific & controlled organization system, DNA would be an unreadable, useless mess. Which means DNA would have to be organized immediately upon creation, or Life couldn't arise. And this is the craziest part... The way DNA is organized in a eukaryotic cell directly controls which genes are turned on or off. This organization is what determines cell-type. Every cell in your body contains the exact same DNA blueprint. The only reason a heart cell beats and a skin cell protects you is due to DNA organization. A heart cell packs away all "skin genes" into tight, unreadable section that doesn't get activated, while keeping "heart genes" open & active. If a cell doesn't have specific DNA organization, it loses its identity. When that happens, it results in cancer. Which means DNA organization must be specifically planned out from the start to prevent catastrophe. Life doesn't have time to tinker and figure this out via evolution. DNA requires organization from the start, or it's useless. DNA organizarion requires multiple systems all working together to function. Without them, it fails. Only intelligence has ever been shown to engineer specifically organized, complex informational systems with obvious signs of preplanning and intentionality. Life was Divinely Designed. Biology proves it over & over again.
0:47

This is how DNA is organized in a cell. And it's more evidence that Life was intelligently designed. Each human cell contains about 6.5ft (2m) of DNA packed into a dense microscopic structure. But it's not packed into a random pile. It's packed into precise loops scientists call 'cohesin loops.' DNA is wound up around spool-like proteins called histones, which are then further wound together into clusters called nucleosomes, which are then organized into shapes called chromatins, which are then folded into large structures called chromosomes. Four levels of very specific, complex organization. Without a specific & controlled organization system, DNA would be an unreadable, useless mess. Which means DNA would have to be organized immediately upon creation, or Life couldn't arise. And this is the craziest part... The way DNA is organized in a eukaryotic cell directly controls which genes are turned on or off. This organization is what determines cell-type. Every cell in your body contains the exact same DNA blueprint. The only reason a heart cell beats and a skin cell protects you is due to DNA organization. A heart cell packs away all "skin genes" into tight, unreadable section that doesn't get activated, while keeping "heart genes" open & active. If a cell doesn't have specific DNA organization, it loses its identity. When that happens, it results in cancer. Which means DNA organization must be specifically planned out from the start to prevent catastrophe. Life doesn't have time to tinker and figure this out via evolution. DNA requires organization from the start, or it's useless. DNA organizarion requires multiple systems all working together to function. Without them, it fails. Only intelligence has ever been shown to engineer specifically organized, complex informational systems with obvious signs of preplanning and intentionality. Life was Divinely Designed. Biology proves it over & over again.

Divinely Designed

13,860 views • 16 days ago

A new Nature paper from Johns Hopkins (by Prof. Lin Dingchang Lin ) just solved one of the hardest problems in biology: how do you record what every cell in a tissue experienced over time, not just what it looks like right now? The answer: GEMINI — Granularly Expanding Memory for Intracellular Narrative Integration. It works exactly like tree rings. Cells are genetically engineered to express a computationally designed protein assembly. As the assembly grows inside the cell, it captures cellular activity as fluorescent ring patterns — each ring a timestamp, each ring's properties encoding signal intensity. Look at a cross-section under a microscope and you can read the cell's history backward, with ~15-minute resolution. The key: cells build the recorder themselves. GEMINI doesn't interfere with normal function — it just quietly writes. What they demonstrated: In a full tumor xenograft, GEMINI captured every cancer cell's activity history across the entire tumor while it continued to grow normally. For the first time, researchers can look back and see how different regions of the same tumor responded differently to therapy over time — not snapshots, but film. In a mouse brain, GEMINI recorded neural activity dynamics without disrupting behavior, coordination, or memory. It could temporally resolve the history of a brain seizure. Why this matters: Every tool we have in biology gives you state — what the cell looks like now. Sequencing, imaging, proteomics — all snapshots. GEMINI gives you trajectory. It's the difference between a photograph and a video, applied to every cell in an organ simultaneously. The team is explicit that AI-based decoding tools will be central to reading GEMINI's output at whole-brain scale. This is the data layer that makes temporal single-cell atlases possible. Paper: Congratulations Dingchang Lin
1:51

A new Nature paper from Johns Hopkins (by Prof. Lin Dingchang Lin ) just solved one of the hardest problems in biology: how do you record what every cell in a tissue experienced over time, not just what it looks like right now? The answer: GEMINI — Granularly Expanding Memory for Intracellular Narrative Integration. It works exactly like tree rings. Cells are genetically engineered to express a computationally designed protein assembly. As the assembly grows inside the cell, it captures cellular activity as fluorescent ring patterns — each ring a timestamp, each ring's properties encoding signal intensity. Look at a cross-section under a microscope and you can read the cell's history backward, with ~15-minute resolution. The key: cells build the recorder themselves. GEMINI doesn't interfere with normal function — it just quietly writes. What they demonstrated: In a full tumor xenograft, GEMINI captured every cancer cell's activity history across the entire tumor while it continued to grow normally. For the first time, researchers can look back and see how different regions of the same tumor responded differently to therapy over time — not snapshots, but film. In a mouse brain, GEMINI recorded neural activity dynamics without disrupting behavior, coordination, or memory. It could temporally resolve the history of a brain seizure. Why this matters: Every tool we have in biology gives you state — what the cell looks like now. Sequencing, imaging, proteomics — all snapshots. GEMINI gives you trajectory. It's the difference between a photograph and a video, applied to every cell in an organ simultaneously. The team is explicit that AI-based decoding tools will be central to reading GEMINI's output at whole-brain scale. This is the data layer that makes temporal single-cell atlases possible. Paper: Congratulations Dingchang Lin

Bo Wang

85,133 views • 4 months ago

🔬 Exciting News! Our manuscript, "scGPT: toward building a foundation model for single-cell multi-omics using generative AI" is now finally published in Nature Methods (Nature Methods) 🎉 !!! (Re-)Introducing scGPT: A transformative foundation model engineered for single-cell omics analysis. Developed through the analysis of over 33 million human cells, scGPT sets a new benchmark for application versatility, offering both fine-tuning and zero-shot capabilities. Since its preprint in May 2023, scGPT has significantly impacted the field, evidenced by 13K+ installations, 600+ GitHub stars 🌟, and 40+ citations before its official publication! scGPT has been validated by numerous benchmark studies as a leading foundation model in single-cell analysis. Its pre-trained embeddings extend its utility beyond single-cell studies, enhancing a variety of downstream tasks including protein enrichment and genetic perturbation predictions. Some key updates lately: ---Expanded zero-shot applications for efficient reference mapping and integration, now with CellXGene census integration. ---Advanced perturbation analysis capabilities, including genome-scale perturb-seq data analysis and bulk sequencing data generalization. ---Upgraded scGPT package, offering versatile model loading compatible with PyTorch and flash-attn, for both GPU and CPU. ---Cloud-based scGPT applications for reference mapping, cell annotation, and gene regulatory network inference are available on ---Integration with Hugging Face for easier model training. Limitations: scGPT is an early foray into foundation models for single-cell omics, facing challenges like limited zero-shot learning in some tasks, pretraining constraints, data quality issues, and evaluation limitations. See our Supplementary Notes for details. 🚀 Future Work? Short-Term Goals: 1. Releasing a Mouse Model for broader analysis. 2. Developing a comprehensive evaluation suite for foundation models in single-cell analysis. 3. Creating a foundation model for single-cell spatial omics. 4. Enhancing zero-shot capacity by integrating scGPT with RAG (e.g., knowledge graphs). Long-Term Goals: 1. Expanding scGPT for comprehensive single-cell multi-omics analysis. 2. Developing an in-silico perturbation model for predicting genetic perturbation effects. 3. Merging scGPT with multi-modal genomic sequence models for a deeper understanding of cell biology. 📚 Access the paper on Nature Methods: 🔬Preprint in Bioarixv: 💻 All our codes/data/weights are open source: Wholehearted congratulations to all the authors, especially the two co-first authors, Haotian (Haotian Cui ) and Chloe (ChloeXWang), who are really the emerging superstars in AI and biology! Vector Institute Peter Munk Cardiac Centre AI U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology University Health Network University of Toronto #scGPT #GenerativeAI #AI4Science #Combio #opensource
0:52

🔬 Exciting News! Our manuscript, "scGPT: toward building a foundation model for single-cell multi-omics using generative AI" is now finally published in Nature Methods (Nature Methods) 🎉 !!! (Re-)Introducing scGPT: A transformative foundation model engineered for single-cell omics analysis. Developed through the analysis of over 33 million human cells, scGPT sets a new benchmark for application versatility, offering both fine-tuning and zero-shot capabilities. Since its preprint in May 2023, scGPT has significantly impacted the field, evidenced by 13K+ installations, 600+ GitHub stars 🌟, and 40+ citations before its official publication! scGPT has been validated by numerous benchmark studies as a leading foundation model in single-cell analysis. Its pre-trained embeddings extend its utility beyond single-cell studies, enhancing a variety of downstream tasks including protein enrichment and genetic perturbation predictions. Some key updates lately: ---Expanded zero-shot applications for efficient reference mapping and integration, now with CellXGene census integration. ---Advanced perturbation analysis capabilities, including genome-scale perturb-seq data analysis and bulk sequencing data generalization. ---Upgraded scGPT package, offering versatile model loading compatible with PyTorch and flash-attn, for both GPU and CPU. ---Cloud-based scGPT applications for reference mapping, cell annotation, and gene regulatory network inference are available on ---Integration with Hugging Face for easier model training. Limitations: scGPT is an early foray into foundation models for single-cell omics, facing challenges like limited zero-shot learning in some tasks, pretraining constraints, data quality issues, and evaluation limitations. See our Supplementary Notes for details. 🚀 Future Work? Short-Term Goals: 1. Releasing a Mouse Model for broader analysis. 2. Developing a comprehensive evaluation suite for foundation models in single-cell analysis. 3. Creating a foundation model for single-cell spatial omics. 4. Enhancing zero-shot capacity by integrating scGPT with RAG (e.g., knowledge graphs). Long-Term Goals: 1. Expanding scGPT for comprehensive single-cell multi-omics analysis. 2. Developing an in-silico perturbation model for predicting genetic perturbation effects. 3. Merging scGPT with multi-modal genomic sequence models for a deeper understanding of cell biology. 📚 Access the paper on Nature Methods: 🔬Preprint in Bioarixv: 💻 All our codes/data/weights are open source: Wholehearted congratulations to all the authors, especially the two co-first authors, Haotian (Haotian Cui ) and Chloe (ChloeXWang), who are really the emerging superstars in AI and biology! Vector Institute Peter Munk Cardiac Centre AI U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology University Health Network University of Toronto #scGPT #GenerativeAI #AI4Science #Combio #opensource

Bo Wang

199,711 views • 2 years ago