Have a Spooktacular Halloween—May Your Experiments Be Free of unidentified beings! #halloween #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
Get directions
4025 Bohannon Dr
Menlo Park, California 94025, US
Employees at Deepcell
Updates
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🌟 Exciting News in the Fight Against Acute Myeloid Leukemia 🌟 Congratulations to Drs. Scott Manalis and Michael Hemann at Massachusetts Institute of Technology and Dr. Andrew Lane at Dana-Farber Cancer Institute (DFCI), for securing a groundbreaking NIH grant to leverage Deepcell technology in advancing acute myeloid leukemia (AML) research! 🎉 This powerful collaboration combines cutting-edge technology with clinical expertise to transform the treatment of minimal/measurable residual disease (MRD). Leveraging Deepcell’s high-content, label-free brightfield imaging and AI-powered sorting, the MIT and DFCI teams will work together to develop a novel platform targeting MRD with unprecedented precision. Their goal? To predict therapeutic response and identify patient-specific vulnerabilities in MRD before relapse, marking a significant step forward in the battle against AML. Together, we are empowering clinicians with real-time insights to shape the future of cancer care. Once again, congratulations to the team, and we can’t wait to see what’s next! 🌱
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Deepcell reposted this
🔬 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
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🔍 How can simply looking at cells through the Deepcell lens guide cancer therapy decisions? In collaboration with AbbVie (data presented at #AACR2024), we demonstrated direct linking between cell morphology to gene expression and function in a lung cancer patient tissue biopsy. 🔬 We identified a rare malignant subpopulation (Cluster 0) with a drastically different gene expression profile compared to the majority of the patient's cancer cells (Cluster 2). 💡 Through sorting, we uncovered key differences in gene expression and pathways, including upregulation of STAT3 (which promotes tumor growth, survival, angiogenesis, immune evasion, and inflammation) and NF-kB signaling (fueling inflammation, tumor survival, resistance to apoptosis, and metastasis) in this rare subpopulation. 🎯 These insights suggest therapeutically targeting STAT3 and NF-kB signaling to effectively combat Cluster 0. The results underscore #REM-I’s potential to unveil hidden cellular subtypes, drive groundbreaking cancer therapies, and transform patient outcomes. Start your journey to harness the power of AI for your application by requesting a demo here: https://lnkd.in/g_nPdRR4 Link to AACR poster here: https://lnkd.in/gF9zA-T4 #PrecisionOncology #CancerResearch #Deepcell #AACR2024 #CancerTherapies #Morpholomics
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Congratulations to Deepcell’s scientific cofounder Prof. Euan Ashley for being appointed as the chair of Stanford Department of Medicine.
Effective Wednesday, September 18, Euan Ashley, MB ChB, DPhil, will be Stanford Department of Medicine's department chair. To get to know him better, we’re sharing a few key facts about Dr. Ashley. 1. Dr. Ashley was born in Scotland and earned his medical degree from the University of Glasgow. He completed his medical residency at Oxford University, where he also received a DPhil in molecular genetics and cardiovascular biology. 2. He was a cardiology fellow at Stanford Department of Medicine before joining the faculty. He has held numerous leadership roles, including founding director of the Stanford Center for Inherited Cardiovascular Disease and director of Catalyst, Stanford’s flagship biomedical innovation program. 3. He is a practicing cardiologist and leads the Ashley Lab, which focuses on the science of precision medicine. His lab is also known to play soccer together! 4. In addition to being the fastest to sequence a human genome — 5 hours and 2 minutes —Dr. Ashley also plays the saxophone, codes, and has solved a Rubik’s cube in 30 seconds. 5. In 2023, Dr. Ashley was awarded a John Simon Guggenheim Fellowship in recognition of his exceptional scholarship and promise. We are thrilled to have Dr. Ashley as our next department leader. Please join us in celebrating his new role and our collective new chapter!
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It is a pleasure to see groundbreaking applications of Deepcell's AI technology highlighted in the discussion organized by Rotterdam Square led by Prof. Peter J. van der Spek. From detecting small numbers of affected cells in blood and urine to enhancing diagnostics across fields like cardiology, oncology, and immunology, Deepcell's AI-enabled solutions continue to push the boundaries of personalized healthcare. "In the time it takes a pathologist to view ten cells and drink a cup of coffee, her AI-enabled colleague can scan up to 100,000 cells and compare them with an extensive library. " Interested to understand how our groundbreaking products can transform your clinical workflows? Reach out to us and request a demo: https://lnkd.in/g_nPdRR4
Yesterday, we hosted our first event after the summer, all about Cutting-Edge Diagnostic Innovations for Enhanced Healthcare Outcomes. It was great to host you all again at Erasmus MC, thank you to everyone who joined us! 𝐏𝐥𝐚𝐲𝐢𝐧𝐠 𝐦𝐞𝐦𝐨𝐫𝐲 𝐰𝐢𝐭𝐡 𝐜𝐞𝐥𝐥𝐬 A challenging dialogue between professors Peter J. van der Spek (Erasmus MC – Bioinformatics) and Evert Stamhuis (Erasmus School of Law – Law & Innovation). Peter enthusiastically introduced applications of Stanford University-based Deepcell AI technology for unprecedentedly fast and powerful #diagnostics in areas as cardiology, oncology, immunology, urology, psychiatry and internal medicine. In the time it takes a pathologist to view ten cells and drink a cup of coffee, her AI-enabled colleague can scan up to 100,000 cells and compare them with an extensive library. which continuously expands as it is used. This makes it possible to detect relatively small numbers of affected cells in body fluids such as blood and urine. Because we have only just begun to explore the amazing possibilities of #AI applications in diagnostics, important normative questions, such as legal and ethical, remain to be answered, Evert explained in his response. Consider #data and technology regulation. Does a photo of a single human cell qualify as personal data, he asked rhetorically. What is the relationship between the public fields of scientific research and healthcare and industry? Who owns the data and algorithms when government agencies upload their images while performing diagnostics? And what healthcare policy priorities exactly are served by the incremental development of technology? The dialogue format of the event once again ensured a lively discussion with the audience, which is guaranteed to continue! We would like to give a special thanks to the Life Sciences & Health delegation from South Africa who joined us at the event and networking yesterday. After a full week of visits throughout the Netherlands, we were very excited to welcome them to #Rotterdam and Erasmus MC to show what is happening here in our vibrant healthcare ecosystem. 📆 Would you like to join our next events? Please visit our website to view our full events calender: https://lnkd.in/euwXYXKy #rotterdamsquare #ecosystem #convergence #lifesciences #health #tech #erasmusmc #erasmusuniversity #erasmusschooloflaw #healthcare #innovation #kadansinnovationpartners #deepcell #multiomics
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Deepcell reposted this
This is incredibly exciting! Will staining be obsolete in the near future? That's certainly what we are seeing with the #rem-i platform at Deepcell. The promise of label-free workflows holds promise for simplifying, streamlining and removing biases from clinical and drug development workflows. As frontiers in AI high resolution brightfield imaging we are excited about these results and insights.
Inside the phenomics - brightfield breakthrough. A new article from Charles Baker, Oren Kraus and Kian Kenyon-Dean provides additional technical insights into our recently developed series of foundation models, called Phenom, and how we trained it on brightfield images to capture nearly all of the biological patterns that can be extracted from CellPaint experiments, while unlocking incredible experimental capabilities. #discovery #science #microscopy #brightfield #ai #techbio #ml #phenomics
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Truly, the natural world hath never been more within our grasp!
If Charles Darwin could visit a modern biology lab, I’m pretty sure he'd need a double espresso after seeing multiomics and AI in action. "Survival of the fittest, huh? Well, this Deepcell #REM-I seems pretty fit!" P.S. All credit to Ideogram for making Darwin's #REM-I moment possible! Happy Friday folks!
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🔬 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
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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/