🔬 Unlocking the Complexity of Cell Death with High-Dimensional Morphology Data Using the REM-I platform, we've captured the intricate and dynamic process of cell death through high-dimensional morphology data. REM-I’s discriminative resolution allows us to identify subtle morphological shifts in the very early and mid-phases of apoptosis. By leveraging deep learning and computer vision, the platform provides orthogonal biological insights that not only complement but often surpass what traditional cytotechnology and protein-based biomarkers can reveal. Check out the visualizations below: (A) Morphology UMAP: Generated by REM-I and colored by cluster using the Leiden algorithm, with representative images included. These morphotype clusters align with morphological changes as cells undergo apoptosis and necrosis. (B) UMAP Visualization: Colored by population density, this visualization demonstrates how different treatments result in varying morphological expressions. Representative images from each treatment condition are displayed below. #Morpholomics #DeepLearning #ComputerVision #CellBiology #Apoptosis #Morphology #Deepcell
About us
Deepcell is pioneering new methods in single cell analysis by combining innovations in microfluidics, optics, and AI. Through these multiple lenses, we are magnifying insights into cells’ phenotype and function to address important research questions across biology.
- Website
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http://www.deepcell.com
External link for Deepcell
- Industry
- Biotechnology Research
- Company size
- 51-200 employees
- Headquarters
- Menlo Park, California
- Type
- Privately Held
Locations
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Primary
4025 Bohannon Dr
Menlo Park, California 94025, US
Employees at Deepcell
Updates
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Deepcell reposted this
🧱 Builders w/ Maddison Masaeli - Co-Founder & CEO @ Deepcell 🚀 Excited to share our latest podcast episode featuring Maddison Masaeli, Co-founder & CEO of @Deepcell! In this insightful conversation, Maddison delves into Deepcell’s innovative approach to single-cell imaging and analysis, shedding light on their groundbreaking technology and its transformative impact on diagnostic testing and therapeutics. Discover how their ambitious project is building the world’s largest database of cellular morphologies and explore the future of precision medicine. Don’t miss this chance to gain valuable insights into the cutting-edge developments shaping the future of healthcare. 🎧 Tune in:
Builders #10 w/ Maddison Masaeli - Co-Founder & CEO @ Deepcell | BIOS
https://www.youtube.com/
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Happy olympics season! #Olympics2024
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🧑🔬 In a new preprint led by investigators at the University of Zurich, melanoma researchers distinguished between melanocytic and mesenchymal cell phenotypes. 🔬 Using label-free high-dimensional morphology profiling, melanoma cell lines were imaged on the REM-I and resulting 115 deep learning and computer vision features were visualized as a reduced dimensionality projection (Figure A). 🔍 Distinct morphotype groups emerged, with melanocytic and mesenchymal cells localizing with respect to a combination of deep learning and morphometric features related to cell texture and size (Figure B-C). 💡 Notably, the REM-I system detected and discerned cells with high pigmentation levels from other melanocytic cells. 🌟 These findings are promising for future applications such as stratifying patient samples based on cell type (Figure B). Check out the preprint available at bioRxiv, titled ”Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling”. 📑
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Deepcell reposted this
Top AI startups to celebrate this #AIAppreciationDay 🤖 These AI startups have been pivotal in driving tech advancements, transforming industries, and redefining the way we live and work. This article highlights the top AI startups that are driving innovation, offering cutting-edge solutions, and shaping the future of AI. 🚀 Anthropic 🚀 Deepcell 🚀 Figure AI 🚀 Graphcore 🚀 Kneron 🚀 Mistral AI 🚀 Stanhope AI 🚀 Wayve 🚀 xAI 🚀 Xaira Therapeutics 👇 Read more below 👇 #StartupsMagazine #Startups #Entrepreneur #AI #AIStartups
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Did you know that deep learning can be used to characterize functional changes in #CRISPR knockout cell lines? 🧬✨🔬 Using REM-i for CRISPR screening allows us to: 🌟 Visualize complex cellular morphologies with high accuracy. 🌟Identify subtle phenotypic changes post-editing. 🌟Quantify functional outcomes efficiently. Here’s a snapshot of our recent findings in collaboration with EMBL: Want to learn more? see https://lnkd.in/gE6RaecT #CRISPR #GeneEditing #DeepLearning #MorphologyProfiling #Biotechnology #ResearchInnovation
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🚀 Exciting news! Our most recent installation at the American Dental Association has been launched into action. We are thrilled to work with Dr. Kevin Matthew Byrd, DDS, PhD’s exceptional team and look forward to the impact the REM-I will have at their Lab of Oral & Craniofacial Innovation! 🦷🔬🌟 #morpholomics #remi #DentalResearch #OralHealth #HealthTech #AmericanDentalAssociation
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🔥 Hot off the press! 🔥 Check out a new pre-print available at bioRxiv lead by Evelyn Lattmann and Mitch Levesque at Universitätsspital Zürich, titled ”Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling”. Using the REM-I system, the group categorized patient-derived melanoma cells into melanocytic and mesenchymal phenotypes. Deepcell REM-I’s AI-enabled label-free method successfully predicted phenotypic shifts, as validated by scRNA-Seq. The study demonstrates a significant link between cell morphology and melanoma cell state, paving the way for AI-informed guidance in oncology applications. The data shows “significant potential for a variety of applications, advancing both biological and clinical research in melanoma”. #REMi #Morpholomics #Melanoma #Oncology #SkinCancer #HealthcareInnovation https://lnkd.in/gyYvBCXF
Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling
biorxiv.org
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Go ADA!
We are excited to share the recent installation of the REM-I instrument in our Lab of Oral & Craniofacial Innovation (LOCI)! The Deepcell REM-I is an advanced AI-powered benchtop instrument that captures high-resolution images of single cells at rapid speeds, all while maintaining a completely label-free workflow. Utilizing Deepcell's Human Foundation Model (HFM), this instrument can extract features from diverse cell images without the need for prior knowledge of specific cell types or markers. The ability to assess 115 dimensions of cell morphology will provide us with deeper insights into cell function and phenotype. As part of first use cases research, we plan to create as many as 100 million images of saliva cell populations over the next 6 months. These samples will come from healthy adults and pediatric subjects, as well as pediatric patients with Inflammatory Bowel Disease (IBD), collected at every follow-up visit. This extensive dataset will enable us to explore and compare the morphological differences in saliva cells across various health states, driving forward our understanding of oral and systemic health connections. We are excited to leverage the REM-I to push the boundaries of oral and craniofacial research, and we look forward to sharing our groundbreaking findings with the scientific community as part of our #IBDSCAN (Inflammatory Bowel Disease Salivary Cell Analysis Network) in collaboration with @Ajay Gulati from samples collected at the University of North Carolina at Chapel Hill Center for Gastrointestinal Biology & Disease led by Dr. Ajay Gulati and supported by the Crohn's & Colitis Foundation #Innovation #AI #Morpholomics #Oralsystemic #Crohns #Deepcell #LOCI #Saliva #IBD
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Deepcell reposted this
We are excited to share the recent installation of the REM-I instrument in our Lab of Oral & Craniofacial Innovation (LOCI)! The Deepcell REM-I is an advanced AI-powered benchtop instrument that captures high-resolution images of single cells at rapid speeds, all while maintaining a completely label-free workflow. Utilizing Deepcell's Human Foundation Model (HFM), this instrument can extract features from diverse cell images without the need for prior knowledge of specific cell types or markers. The ability to assess 115 dimensions of cell morphology will provide us with deeper insights into cell function and phenotype. As part of first use cases research, we plan to create as many as 100 million images of saliva cell populations over the next 6 months. These samples will come from healthy adults and pediatric subjects, as well as pediatric patients with Inflammatory Bowel Disease (IBD), collected at every follow-up visit. This extensive dataset will enable us to explore and compare the morphological differences in saliva cells across various health states, driving forward our understanding of oral and systemic health connections. We are excited to leverage the REM-I to push the boundaries of oral and craniofacial research, and we look forward to sharing our groundbreaking findings with the scientific community as part of our #IBDSCAN (Inflammatory Bowel Disease Salivary Cell Analysis Network) in collaboration with @Ajay Gulati from samples collected at the University of North Carolina at Chapel Hill Center for Gastrointestinal Biology & Disease led by Dr. Ajay Gulati and supported by the Crohn's & Colitis Foundation #Innovation #AI #Morpholomics #Oralsystemic #Crohns #Deepcell #LOCI #Saliva #IBD
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