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I'm prototyping a little tool for interactively visualizing the near-nearest neighbor network in single-cell RNA-seq. Clicking a cell triggers a wave, revealing its nearest neighbors, then their neighbors, and so forth. Data: 10k PBMCs from a Healthy Donor (v3), 10x Genomics

Brad Krajina

1,778 subscribers

36,054 görüntüleme • 1 yıl önce •via X (Twitter)

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Brad Krajina profil fotoğrafı

Brad Krajina1 yıl önce

This visualization was made in TypeScript with PixiJS and captured in real-time in a browser.

PDF GPT profil fotoğrafı

PDF GPT2 yıl önce

This is my favorite AI tool for reviewing reports. Just upload a report, ask for a summary, and get one in seconds. It's like ChatGPT, but built for documents. Try it for free.

Thomas Czerniawski profil fotoğrafı

Thomas Czerniawski1 yıl önce

So exciting to see new ways to poke and prod at higher dimensions

Brad Krajina profil fotoğrafı

Brad Krajina1 yıl önce

Thanks Thomas! With the scale and dimensionality of the data we're dealing with today, I think there is so much room for re-thinking the way that we interface it.

Garry P. Nolan profil fotoğrafı

Garry P. Nolan1 yıl önce

Fantastic!

⌬Michel Rickhaus profil fotoğrafı

⌬Michel Rickhaus1 yıl önce

Gorgeous!

Brad Krajina profil fotoğrafı

Brad Krajina1 yıl önce

Thank you!

Jeffrey West profil fotoğrafı

Jeffrey West1 yıl önce

this is cool!

Brad Krajina profil fotoğrafı

Brad Krajina1 yıl önce

Thanks Jeffrey!

Curtis profil fotoğrafı

Curtis1 yıl önce

This is really cool!!

Brad Krajina profil fotoğrafı

Brad Krajina1 yıl önce

Thanks Curtis!

Benzer Videolar

I'm creating 3D tours of open single cell RNA-seq data in UMAP space. Here, using data from 50k brain cells by the allen institute . ( The UMAP position and class of every cell is read into Blender, realized as a stylized, class-specific model I sculpted

I'm creating 3D tours of open single cell RNA-seq data in UMAP space. Here, using data from 50k brain cells by the allen institute . ( The UMAP position and class of every cell is read into Blender, realized as a stylized, class-specific model I sculpted

Brad Krajina

48,151 görüntüleme • 3 yıl önce

🔬 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

🔬 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

199,790 görüntüleme • 2 yıl önce

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.

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

58,492 görüntüleme • 1 yıl önce

🚀 Introducing PantheonOS ( A Fully Open-Source Agent OS for Science PantheonOS began as a research project in my Stanford lab and has since evolved into a vision to redefine data science in the era of AI—starting with computational biology, especially single-cell and spatial genomics. PantheonOS is a general agent platform built from the ground up. It is arguably the first distributed agent framework designed for scientific data analysis. 🔑 Key Features 1. Multi-Agent Collaboration – Built-in paradigms for distributed, cross-machine cooperation among agents and toolsets. 2. Native Toolset Support – Python, R, Julia, LaTeX, and more—designed for real scientific workflows. 3. Modular & Extensible – Developer-friendly design with shallow wrappers, plus LLM-driven toolset generation. 4. Evolvable Agents – Capable of evolving large-scale code projects to achieve superhuman performance (e.g., evolving upon the original Harmony [I Korsunsky, 2019, Nature Biotechnology] and Scanorama [BL Hie, 2019, Nature Biotechnology] implementations), and even evolving the system itself to adapt to new fields. 🎉 Stepwise Release Strategy We’re releasing PantheonOS in stages: Pantheon-CLI (today!), followed by Pantheon-Lab, Pantheon-Notebook, Pantheon-Slack, and more. 🌟 Pantheon-CLI Highlights - We're not just building another CLI tool. We're defining how scientists will interact with data in the AI era. - Open, Powerful, Python-First – The first fully open-source, endlessly extendable scientific “vibe analysis” framework. - Mixed Programming Magic – Combine Python, natural language, R, or Julia—seamlessly in the same environment. - PhD-Level Assistant – A command-line agent for complex real-world genomics and beyond, handling workflows at the PhD level. - Privacy by Design – Run entirely offline with local LLMs—your data never leaves your computer. ✅ Proven Applications (10 Demonstrations) Computational biology: 1. ATAC-seq: From raw reads to peak matrix 2. RNA-seq: From raw reads to expression matrix 3. Complex single-cell workflows (PhD-level) 4. Hybrid natural language + R for Seurat annotation 5. Learning from web tutorials + invoking single-cell foundation models 6. Cell segmentation on 10x Genomics HD Visium data And beyond: 7. Mixed Python & R programming examples 8. Molecular docking & structural analysis 9. Exploratory factor analysis for behavioral survey data 10. Customer segmentation & finance analytics 🌐 Learn More & Get Started Website: Pantheon-CLI Documentation: GitHub Repo: 💬 Join our community: PantheonOS Slack: PantheonOS Discord:

🚀 Introducing PantheonOS ( A Fully Open-Source Agent OS for Science PantheonOS began as a research project in my Stanford lab and has since evolved into a vision to redefine data science in the era of AI—starting with computational biology, especially single-cell and spatial genomics. PantheonOS is a general agent platform built from the ground up. It is arguably the first distributed agent framework designed for scientific data analysis. 🔑 Key Features 1. Multi-Agent Collaboration – Built-in paradigms for distributed, cross-machine cooperation among agents and toolsets. 2. Native Toolset Support – Python, R, Julia, LaTeX, and more—designed for real scientific workflows. 3. Modular & Extensible – Developer-friendly design with shallow wrappers, plus LLM-driven toolset generation. 4. Evolvable Agents – Capable of evolving large-scale code projects to achieve superhuman performance (e.g., evolving upon the original Harmony [I Korsunsky, 2019, Nature Biotechnology] and Scanorama [BL Hie, 2019, Nature Biotechnology] implementations), and even evolving the system itself to adapt to new fields. 🎉 Stepwise Release Strategy We’re releasing PantheonOS in stages: Pantheon-CLI (today!), followed by Pantheon-Lab, Pantheon-Notebook, Pantheon-Slack, and more. 🌟 Pantheon-CLI Highlights - We're not just building another CLI tool. We're defining how scientists will interact with data in the AI era. - Open, Powerful, Python-First – The first fully open-source, endlessly extendable scientific “vibe analysis” framework. - Mixed Programming Magic – Combine Python, natural language, R, or Julia—seamlessly in the same environment. - PhD-Level Assistant – A command-line agent for complex real-world genomics and beyond, handling workflows at the PhD level. - Privacy by Design – Run entirely offline with local LLMs—your data never leaves your computer. ✅ Proven Applications (10 Demonstrations) Computational biology: 1. ATAC-seq: From raw reads to peak matrix 2. RNA-seq: From raw reads to expression matrix 3. Complex single-cell workflows (PhD-level) 4. Hybrid natural language + R for Seurat annotation 5. Learning from web tutorials + invoking single-cell foundation models 6. Cell segmentation on 10x Genomics HD Visium data And beyond: 7. Mixed Python & R programming examples 8. Molecular docking & structural analysis 9. Exploratory factor analysis for behavioral survey data 10. Customer segmentation & finance analytics 🌐 Learn More & Get Started Website: Pantheon-CLI Documentation: GitHub Repo: 💬 Join our community: PantheonOS Slack: PantheonOS Discord:

evo-devo

17,439 görüntüleme • 1 yıl önce

NEW: Florida Governor Ron DeSantis shreds Tim Walz for setting up a COVID hotline so neighbors could snitch on each other. The comment came after Walz said people should “respect” their neighbors and “mind their own d*mn business.” “He's got this line in the stump speech saying, you know, our neighbors can do what they want. Mind your own d*mn business.” “Fine. Then why did you set up a snitch hotline for neighbors to report on their neighbors for violating your draconian covid restrictions? That's not minding your own d*mn business. That's government overreach.”

NEW: Florida Governor Ron DeSantis shreds Tim Walz for setting up a COVID hotline so neighbors could snitch on each other. The comment came after Walz said people should “respect” their neighbors and “mind their own dmn business.” “He's got this line in the stump speech saying, you know, our neighbors can do what they want. Mind your own dmn business.” “Fine. Then why did you set up a snitch hotline for neighbors to report on their neighbors for violating your draconian covid restrictions? That's not minding your own d*mn business. That's government overreach.”

Collin Rugg

1,655,469 görüntüleme • 2 yıl önce

Out today: Researchers have made the first cell capable of “feeding, growth, replication, division and selection...entirely using components scientists put there.” In other words, a cell that self-replicates and was made entirely from the ground-up, molecule by molecule. The cell is called SpudCell. And although it is definitely a cell (in that it has a membrane with molecules inside) it is definitely not alive, because it cannot grow indefinitely, survive without human help, make its own ribosomes, or recycle waste. It "dies" after a few divisions. But it's a starting point! And these same researchers have raised $6-8M+ in philanthropic funding to scale their efforts with a new nonprofit for synthetic cell research, called Biotic.

Out today: Researchers have made the first cell capable of “feeding, growth, replication, division and selection...entirely using components scientists put there.” In other words, a cell that self-replicates and was made entirely from the ground-up, molecule by molecule. The cell is called SpudCell. And although it is definitely a cell (in that it has a membrane with molecules inside) it is definitely not alive, because it cannot grow indefinitely, survive without human help, make its own ribosomes, or recycle waste. It "dies" after a few divisions. But it's a starting point! And these same researchers have raised $6-8M+ in philanthropic funding to scale their efforts with a new nonprofit for synthetic cell research, called Biotic.

Niko McCarty.

123,933 görüntüleme • 2 ay önce

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.

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

388,342 görüntüleme • 9 ay önce

POV: you hear a ruckus at the neighbors' house, but it's nothing exciting so you take a nap on the porch. Video: an Eastern screech owl appears from the depths of its nest hole and slowly settles in for a rest in the entrance. By Chris Quezada/USFWS

POV: you hear a ruckus at the neighbors' house, but it's nothing exciting so you take a nap on the porch. Video: an Eastern screech owl appears from the depths of its nest hole and slowly settles in for a rest in the entrance. By Chris Quezada/USFWS

U.S. Fish and Wildlife Service

13,887 görüntüleme • 2 yıl önce

Toronto Police launched Project Lighthouse in November, 2025 after police were tipped off about an unknown person(s) operating an SMS Blaster in downtown Toronto. Watch the video for an actual explanation. The fancy Detective lady gives a run down on what happened. tl;dr three chinese dudes some how built a custom made portable cell phone tower thingie in a van, drove around toronto with it. peoples cell phones automagically connected it to (its literally a cell phone tower thingie). when a cell phone connected to their portable cell tower thingie it would automatically send the connected phone a text which appeared to be from their bank or somewhere important. they interupted real cell phone towers 13m times lmfao. they were trying to steal passwords and stuff. no details released on how three random nerds managed to do this

Toronto Police launched Project Lighthouse in November, 2025 after police were tipped off about an unknown person(s) operating an SMS Blaster in downtown Toronto. Watch the video for an actual explanation. The fancy Detective lady gives a run down on what happened. tl;dr three chinese dudes some how built a custom made portable cell phone tower thingie in a van, drove around toronto with it. peoples cell phones automagically connected it to (its literally a cell phone tower thingie). when a cell phone connected to their portable cell tower thingie it would automatically send the connected phone a text which appeared to be from their bank or somewhere important. they interupted real cell phone towers 13m times lmfao. they were trying to steal passwords and stuff. no details released on how three random nerds managed to do this

vx-underground

75,752 görüntüleme • 4 ay önce

Evolution says you can turn anything into anything if you tweak it long enough. But that house of cards collapses immediately when you realize what it takes to make even a single cell. They say new cell types arise one mutation at a time. Is that plausible? Here is the issue: Different cell types are created through a massive coordinated stack of genetic information, and it's not all just about DNA sequences. First you need a whole suite of new genetic systems related to the cell: new genes for the cell’s internal systems, instructions for its specific functional role in the body, the regulators that coordinate everything, markers to tell them where to go and when, and the controls that keep the wrong programs off. But the DNA structure itself must also be manipulated. You see, every cell in your body contains the DNA instructions to make any other cell. So how does a bone cell become a bone cell instead of a skin cell? Because of how the DNA is folded. DNA is folded in certain ways for different cell types, so that only the "bone cell instructions" are able to be read by the "cell construction program." The DNA fold decides which programs are open for each cell type. This is critical. If DNA is not folded properly so that specific cell-type information can be read, catastrophe ensues. Then you need placement blueprints, so the cells form in the right place, in the right number, and lock together to form a functional tissue. These developmental instructions are passed from parent to offspring - but research shows that tweaking these master developmental programs ends badly for the child. One mutation at a time cannot invent that entire programming stack and keep it coordinated. Research has confirmed this. To convert one cell type into another in the lab, researchers have to force many changes to happen at the same time in coordination. And even when directed by the researcher, cell conversion almost always fails. Change the sequence without the fold and you cannot get a new cell type. Fold the DNA without the new systems and you can only rearrange old programs. Make the cell without the map and it shows up in the wrong place. Break one layer in the stack and the others do not patiently wait - they fail. So creating a new cell type is not simply "tweak a gene one at a time." It requires a coordinated stack of entirely new programmed instructions: > New suite of internal systems, programmed into the DNA > New functional DNA fold so only the right systems are activated > New mapping blueprints so everything goes where it's needed Step-by-step mutation does not coordinate those layers. It produces broken cells before it produces new ones. Coordination of this level of complexity has only ever been known to come from one place: Intelligence.

Evolution says you can turn anything into anything if you tweak it long enough. But that house of cards collapses immediately when you realize what it takes to make even a single cell. They say new cell types arise one mutation at a time. Is that plausible? Here is the issue: Different cell types are created through a massive coordinated stack of genetic information, and it's not all just about DNA sequences. First you need a whole suite of new genetic systems related to the cell: new genes for the cell’s internal systems, instructions for its specific functional role in the body, the regulators that coordinate everything, markers to tell them where to go and when, and the controls that keep the wrong programs off. But the DNA structure itself must also be manipulated. You see, every cell in your body contains the DNA instructions to make any other cell. So how does a bone cell become a bone cell instead of a skin cell? Because of how the DNA is folded. DNA is folded in certain ways for different cell types, so that only the "bone cell instructions" are able to be read by the "cell construction program." The DNA fold decides which programs are open for each cell type. This is critical. If DNA is not folded properly so that specific cell-type information can be read, catastrophe ensues. Then you need placement blueprints, so the cells form in the right place, in the right number, and lock together to form a functional tissue. These developmental instructions are passed from parent to offspring - but research shows that tweaking these master developmental programs ends badly for the child. One mutation at a time cannot invent that entire programming stack and keep it coordinated. Research has confirmed this. To convert one cell type into another in the lab, researchers have to force many changes to happen at the same time in coordination. And even when directed by the researcher, cell conversion almost always fails. Change the sequence without the fold and you cannot get a new cell type. Fold the DNA without the new systems and you can only rearrange old programs. Make the cell without the map and it shows up in the wrong place. Break one layer in the stack and the others do not patiently wait - they fail. So creating a new cell type is not simply "tweak a gene one at a time." It requires a coordinated stack of entirely new programmed instructions: > New suite of internal systems, programmed into the DNA > New functional DNA fold so only the right systems are activated > New mapping blueprints so everything goes where it's needed Step-by-step mutation does not coordinate those layers. It produces broken cells before it produces new ones. Coordination of this level of complexity has only ever been known to come from one place: Intelligence.

Divinely Designed

22,570 görüntüleme • 21 gün önce

Your neighbor claims that part of your property is actually theirs, you two go back and forth. You then decide to just put a fence up, during the process the neighbors install cameras so they know when you are coming and going, they put a tent on your property so they can watch you and even go as far as hire a company to take down your fence. They end up building their own fence but you know it’s far from over, should you take legal recourse for damages?

Your neighbor claims that part of your property is actually theirs, you two go back and forth. You then decide to just put a fence up, during the process the neighbors install cameras so they know when you are coming and going, they put a tent on your property so they can watch you and even go as far as hire a company to take down your fence. They end up building their own fence but you know it’s far from over, should you take legal recourse for damages?

SonnyBoy🇺🇸

2,025,168 görüntüleme • 8 ay önce

The Bitter Lesson for Biology — Adam Green on Scaling Laws for Virtual Cells In this episode, the founder of Markov Biosciences, Adam Green, explains the "bitter lesson" for biology, the idea borrowed from Richard Sutton that large unbiased datasets and the right training objective tend to outcompete models with hard-coded rules and human priors. We talk a lot about virtual cells, sources of bias in data, and his evidence that virtual cells pre-trained on plain observational data show clean scaling laws, getting monotonically better at predicting unseen perturbations as the models grow, and beating a state-of-the-art model built specifically for that task. Our interview was about 3 hours long, but cut to 1.5 hours. My main goal was to understand Adam's perspective on virtual cells and his goal to "solve biology." Search for "The New Biology" on YouTube, Spotify, and Apple Podcasts. Timestamps: 00:00 — Cold open 01:58 — Clinical predictions from a virtual cell 05:38 — What is a "virtual cell"? 08:01 — The problems with single-cell RNA-seq 11:31 — The urns analogy 19:54 — Observational vs. perturbation 23:29 — The bitter lesson for biology 29:06 — Geometric Plackett-Luce 38:27 — Ablations and loss function 47:23 — Cells as specimens 59:26 — Antibody-Drug conjugates 1:11:16 — Will we ever understand the cell fully?

The Bitter Lesson for Biology — Adam Green on Scaling Laws for Virtual Cells In this episode, the founder of Markov Biosciences, Adam Green, explains the "bitter lesson" for biology, the idea borrowed from Richard Sutton that large unbiased datasets and the right training objective tend to outcompete models with hard-coded rules and human priors. We talk a lot about virtual cells, sources of bias in data, and his evidence that virtual cells pre-trained on plain observational data show clean scaling laws, getting monotonically better at predicting unseen perturbations as the models grow, and beating a state-of-the-art model built specifically for that task. Our interview was about 3 hours long, but cut to 1.5 hours. My main goal was to understand Adam's perspective on virtual cells and his goal to "solve biology." Search for "The New Biology" on YouTube, Spotify, and Apple Podcasts. Timestamps: 00:00 — Cold open 01:58 — Clinical predictions from a virtual cell 05:38 — What is a "virtual cell"? 08:01 — The problems with single-cell RNA-seq 11:31 — The urns analogy 19:54 — Observational vs. perturbation 23:29 — The bitter lesson for biology 29:06 — Geometric Plackett-Luce 38:27 — Ablations and loss function 47:23 — Cells as specimens 59:26 — Antibody-Drug conjugates 1:11:16 — Will we ever understand the cell fully?

Niko McCarty.

28,208 görüntüleme • 3 ay önce

Today marks a historic moment for Kyivstar, as it becomes the first mobile operator in Europe to launch Starlink Direct to Cell satellite technology for its customers in Ukraine. Now, all Kyivstar customers in Ukraine with 4G smartphones can stay connected through Starlink Direct to Cell, even when the terrestrial network is not available. First through SMS, and later with voice and data, this technology isn’t just back up technology - it’s a new definition of resilience to keep Ukraine connected. Find out more ⬇️

Today marks a historic moment for Kyivstar, as it becomes the first mobile operator in Europe to launch Starlink Direct to Cell satellite technology for its customers in Ukraine. Now, all Kyivstar customers in Ukraine with 4G smartphones can stay connected through Starlink Direct to Cell, even when the terrestrial network is not available. First through SMS, and later with voice and data, this technology isn’t just back up technology - it’s a new definition of resilience to keep Ukraine connected. Find out more ⬇️

VEON

1,447,397 görüntüleme • 9 ay önce

My neighbor lets the cat they adopted from the streets as a kitten go outside for a while every day so it doesn't feel lonely and can play with its old friends from the streets. When it's time to come home, the cat goes under the balcony and meows to let its owner know. My neighbor then lowers a special basket they made for the cat from the balcony and brings their little friend back inside. Would you just look at how adorable this is? 🥹❤️

My neighbor lets the cat they adopted from the streets as a kitten go outside for a while every day so it doesn't feel lonely and can play with its old friends from the streets. When it's time to come home, the cat goes under the balcony and meows to let its owner know. My neighbor then lowers a special basket they made for the cat from the balcony and brings their little friend back inside. Would you just look at how adorable this is? 🥹❤️

Dailymeow

1,132,500 görüntüleme • 1 ay önce

🇪🇺🇷🇺 For EU's Kaja Kallas, Russia is ALWAYS the issue: "It has been attacking its neighbors for over a hundred years" "So in order to stop the war and prevent it from expanding, we should have concessions on the Russian side"

🇪🇺🇷🇺 For EU's Kaja Kallas, Russia is ALWAYS the issue: "It has been attacking its neighbors for over a hundred years" "So in order to stop the war and prevent it from expanding, we should have concessions on the Russian side"

Lord Bebo

24,003 görüntüleme • 7 ay önce

The first morning in a new apartment is supposed to be about coffee and unpacking boxes, not dealing with a final boss level Karen. Imagine moving in and immediately being met with a neighbor who thinks she’s the border patrol of the complex. It’s the blatant audacity to shout “go back to Jamaica” while holding a dog like a tactical weapon for us. The “neighbor from hell” trope isn’t just a movie plot; it’s a living, breathing reality in broad daylight. This is why people don’t know their neighbors anymore.

The first morning in a new apartment is supposed to be about coffee and unpacking boxes, not dealing with a final boss level Karen. Imagine moving in and immediately being met with a neighbor who thinks she’s the border patrol of the complex. It’s the blatant audacity to shout “go back to Jamaica” while holding a dog like a tactical weapon for us. The “neighbor from hell” trope isn’t just a movie plot; it’s a living, breathing reality in broad daylight. This is why people don’t know their neighbors anymore.

✨️Serenitee♡Sam✨️

12,876 görüntüleme • 4 ay önce

Today, SpaceX successfully deployed 20 actual Starlink V3 satellites for the first time ever. Starship V3 can hold up to 60 of these satellites. Each Starlink V3 satellite offers 1 Tbps of downlink capacity, so a single Starship launch can add up to 60 Tbps of total downlink capacity to the network which is more than 20x what a Falcon 9 delivers today with V2 satellites. Insane scale. V3 will also enable 5G high-bandwidth direct-to-cell connectivity anywhere in the world. After deployment, SpaceX successfully made contact with all 20 Satellites! Successful day.

Today, SpaceX successfully deployed 20 actual Starlink V3 satellites for the first time ever. Starship V3 can hold up to 60 of these satellites. Each Starlink V3 satellite offers 1 Tbps of downlink capacity, so a single Starship launch can add up to 60 Tbps of total downlink capacity to the network which is more than 20x what a Falcon 9 delivers today with V2 satellites. Insane scale. V3 will also enable 5G high-bandwidth direct-to-cell connectivity anywhere in the world. After deployment, SpaceX successfully made contact with all 20 Satellites! Successful day.

Nic Cruz Patane

106,801 görüntüleme • 1 ay önce

🚨🚨🚨The first week of rapper Lil Durk’s trial has officially come to a close. Taylor Parise reports: The defense finished its cross-examination of Kacey Hester, also known as OTF Jam, while the government’s redirect led to a tense back-and-forth between both sides. Jurors also heard more about cell phone location data, as the defense pointed to another alleged inconsistency in testimony from Jam.

🚨🚨🚨The first week of rapper Lil Durk’s trial has officially come to a close. Taylor Parise reports: The defense finished its cross-examination of Kacey Hester, also known as OTF Jam, while the government’s redirect led to a tense back-and-forth between both sides. Jurors also heard more about cell phone location data, as the defense pointed to another alleged inconsistency in testimony from Jam.

Los Angeles Magazine

47,510 görüntüleme • 20 gün önce

White bicyclist on his cell phone in NYC blocks a black garbage man and his garbage truck from doing their job. This enrages me. People work hard to do their jobs and the right thing, then get punished for it for no good reason. Props to the garbage man for showing restraint.

White bicyclist on his cell phone in NYC blocks a black garbage man and his garbage truck from doing their job. This enrages me. People work hard to do their jobs and the right thing, then get punished for it for no good reason. Props to the garbage man for showing restraint.

Paul A. Szypula 🇺🇸

1,220,877 görüntüleme • 1 yıl önce