Genie TechBio Inc.

If you’re working in or on omics and happen to be in #Berlin on November 21, join us for an evening of drinks and biotech networking! 🍻 Whether you’re in genomics, proteomics, transcriptomics—or anything in between—come by to share insights, explore potential collaborations, or just enjoy a beer with the local biotech community. We look forward to meeting fellow researchers, founders, and industry pros making strides in omics! 👉 Sign up here to let us know you’re coming: https://lu.ma/lt4sy32w

𝗨𝗠𝗔𝗣 𝘃𝘀 𝗣𝗖𝗔 𝗶𝗻 𝘀𝗰𝗥𝗡𝗔-𝘀𝗲𝗾: 𝗞𝗲𝘆 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗮𝗻𝗱 𝗖𝗼𝗺𝗺𝗼𝗻 𝗠𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴𝘀 When analyzing #scRNAseq data, #PCA (Principal Component Analysis) and #UMAP (Uniform Manifold Approximation and Projection) are essential tools for dimensionality reduction, but they serve different purposes. 🔍 𝗣𝗖𝗔: Linear method that finds the directions (principal components) with the most variance. 𝗕𝗲𝘀𝘁 𝗳𝗼𝗿: Understanding overall data variance and trends. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗺𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: “PCA should always separate cell types clearly.” PCA captures large-scale variance, which might be technical noise, not necessarily biological differences. 🔍 𝗨𝗠𝗔𝗣: Non-linear method that preserves local relationships between cells. 𝗕𝗲𝘀𝘁 𝗳𝗼𝗿: Visualizing cell clusters and complex data structures. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗺𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: “UMAP distance equals biological distance.” UMAP focuses on local structures, so distances between clusters may not directly reflect biological differences. 𝗞𝗲𝘆 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀: 𝗟𝗶𝗻𝗲𝗮𝗿 𝘃𝘀 𝗡𝗼𝗻-𝗹𝗶𝗻𝗲𝗮𝗿: PCA finds linear relationships, while UMAP captures complex, non-linear structures. 𝗩𝗮𝗿𝗶𝗮𝗻𝗰𝗲 𝘃𝘀 𝗡𝗲𝗶𝗴𝗵𝗯𝗼𝗿𝗵𝗼𝗼𝗱 𝗣𝗿𝗲𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝗼𝗻: PCA maximizes variance, UMAP preserves local relationships, making it better for clustering. 𝗚𝗹𝗼𝗯𝗮𝗹 𝘃𝘀 𝗟𝗼𝗰𝗮𝗹: PCA captures global trends, UMAP excels at revealing small, closely related cell populations. 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Use #PCA for an initial overview and #UMAP for detailed exploration of cell types and relationships. Remember: these tools guide you, but always validate your findings with biological markers. 🔗 At Genie TechBio Inc., we help streamline #scRNAseq analysis so you can focus on the #biology. Interested in learning more? Let's connect!

🔍 𝗖𝗮𝗻 𝗚𝗣𝗧-𝟰 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝘆 𝗜𝗺𝗽𝗿𝗼𝘃𝗲 𝗖𝗲𝗹𝗹 𝗧𝘆𝗽𝗲 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗶𝗻𝗴𝗹𝗲-𝗖𝗲𝗹𝗹 𝗥𝗡𝗔-𝘀𝗲𝗾 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀? A recent Nature Methods publication by Wenpin H. (Columbia University) and zhicheng ji (Duke University School of Medicine) demonstrates that #GPT-4 can accurately and efficiently annotate cell types in #scRNAseq data, with results closely aligning with manual annotations in over 75% of cases. 𝗞𝗲𝘆 𝗵𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 𝙊𝙥𝙩𝙞𝙢𝙞𝙯𝙚𝙙 𝙬𝙞𝙩𝙝 𝙩𝙝𝙚 𝙩𝙤𝙥 10 𝙙𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩𝙞𝙖𝙡 𝙜𝙚𝙣𝙚𝙨: GPT-4 performs best using differential genes derived from the Wilcoxon test. 𝙒𝙞𝙙𝙚 𝙖𝙥𝙥𝙡𝙞𝙘𝙖𝙗𝙞𝙡𝙞𝙩𝙮:It excels in annotating immune cells and major cell types like T cells, while providing granular insights for more complex cell types. 𝙎𝙥𝙚𝙚𝙙 𝙖𝙣𝙙 𝙚𝙛𝙛𝙞𝙘𝙞𝙚𝙣𝙘𝙮: Integrating directly into analysis pipelines like #Seurat, #GPT4 is faster and more cost-effective than traditional methods. 𝙍𝙤𝙗𝙪𝙨𝙩𝙣𝙚𝙨𝙨 𝙞𝙣 𝙘𝙤𝙢𝙥𝙡𝙚𝙭 𝙨𝙘𝙚𝙣𝙖𝙧𝙞𝙤𝙨: Even with noisy or mixed data, #GPT4 maintains high reproducibility, distinguishing pure from mixed cell types with 93% accuracy. Despite its strengths, human validation remains key to avoid AI errors and ensure accuracy. Could fine-tuning GPT-4 with curated gene lists further boost its performance? How can researchers balance automation with expert oversight in large datasets? Read the full paper here: https://lnkd.in/eF2SCSkx #Bioinformatics #SingleCell #AI #scRNAseq #NatureMethods #GPT4 #GeneAnnotation

𝗘𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗢𝗺𝗶𝗰𝘀 𝗶𝗻 𝗖𝗲𝗹𝗹 𝗧𝗵𝗲𝗿𝗮𝗽𝘆 #Celltherapy stands at the cutting edge of medical innovation, offering hope for treating complex diseases like cancer and #autoimmunedisorders. By harnessing the body’s own cells—or engineering them for enhanced functionality—#celltherapy aims to restore and maintain health in unprecedented ways. But to fully unlock its potential, omics technologies are proving to be the game-changer. 𝙒𝙝𝙮 #𝙊𝙢𝙞𝙘𝙨 𝙞𝙨 𝘾𝙧𝙪𝙘𝙞𝙖𝙡 𝙛𝙤𝙧 𝙩𝙝𝙚 𝘼𝙙𝙫𝙖𝙣𝙘𝙚𝙢𝙚𝙣𝙩 𝙤𝙛 𝘾𝙚𝙡𝙡 𝙏𝙝𝙚𝙧𝙖𝙥𝙮: #𝙂𝙚𝙣𝙤𝙢𝙞𝙘 𝙄𝙣𝙨𝙞𝙜𝙝𝙩𝙨: Deep genomic analysis enables us to assess genetic modifications in engineered cells, ensuring they function as designed. This level of understanding not only improves therapeutic precision but also helps minimize risks associated with off-target effects. #𝙏𝙧𝙖𝙣𝙨𝙘𝙧𝙞𝙥𝙩𝙞𝙤𝙣𝙖𝙡 𝙋𝙧𝙤𝙛𝙞𝙡𝙞𝙣𝙜: By tracking #geneexpression patterns, researchers can evaluate how different cell types respond to treatments. This helps tailor therapies to individual patient profiles, maximizing efficacy and minimizing adverse effects. #𝙋𝙧𝙤𝙩𝙚𝙤𝙢𝙞𝙘 𝙈𝙖𝙧𝙠𝙚𝙧𝙨: Monitoring the proteins that cells express provides critical insights into their functionality. These markers can indicate whether a cell therapy is working as intended and help clinicians adjust treatments based on real-time patient responses. #𝙈𝙚𝙩𝙖𝙗𝙤𝙡𝙞𝙘 𝙏𝙧𝙖𝙘𝙠𝙞𝙣𝙜: #Metabolism offers a window into cell health. Understanding shifts in #metabolic pathways allows researchers to fine-tune #therapies for optimal cell viability, ensuring that treatments not only work in the short term but also sustain long-term benefits. At Genie TechBio Inc., we’re helping to drive this innovation forward. By enabling #biologists to analyze #omics data without the need for coding, we’re making it easier to uncover the #genomic, #transcriptomic, #proteomic, and metabolic insights necessary to refine and #personalize #celltherapies. With our AI bioinformatician, researchers can explore complex datasets with ease, empowering them to make breakthroughs faster and more efficiently. The integration of #multiomics into cell therapy is far from a passing trend—it’s becoming the cornerstone for safer, more effective treatments. As we continue to refine these tools, we move closer to fully #personalizedtherapies, designed to meet the unique needs of each patient. 🔍 Curious to learn more about the companies at the forefront of this space? Check out these pioneers driving innovation in #CellTherapy and #Omics: CARGO Therapeutics, ADAPTIMMUNE THERAPEUTICS PLC, Atara Biotherapeutics, Aspen Neuroscience, Inc., MaxCyte, Inc., Gamida Cell Ltd., Allogene Therapeutics, Anixa Biosciences, Inc., Autolus Therapeutics, Cartesian Therapeutics, Kite Pharma, Legend Biotech

We are sure that we are in the right path with these double prizes from Physics yesterday, and now Chemistry!

🌟 𝗡𝗼𝗯𝗲𝗹 𝗣𝗿𝗶𝘇𝗲 𝗶𝗻 𝗣𝗵𝘆𝘀𝗶𝗰𝘀 𝟮𝟬𝟮𝟰: 𝗣𝗶𝗼𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗔𝗜 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗺𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗧𝗵𝗲𝗶𝗿 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗻 𝗕𝗶𝗼𝘁𝗲𝗰𝗵 🌟 This year’s #Nobel Laureates in #Physics, 𝗝𝗼𝗵𝗻 𝗛𝗼𝗽𝗳𝗶𝗲𝗹𝗱 and 𝗚𝗲𝗼𝗳𝗳𝗿𝗲𝘆 𝗛𝗶𝗻𝘁𝗼𝗻, have been honored for their foundational work in #artificialneuralnetworks — the technology that underpins much of today’s #machinelearning. Their research, combining insights from #physics and #computationalmodels, laid the groundwork for innovations that are transforming industries, including #biotechnology. 𝗛𝗼𝗽𝗳𝗶𝗲𝗹𝗱's #associative #memory #model and 𝗛𝗶𝗻𝘁𝗼𝗻's development of the #Boltzmann #machine have enabled machines to learn from #data, recognize patterns, and evolve autonomously. These principles of #AI, once inspired by the #brain's #neural structures, are now essential in fields like #biomedicine, helping decode complex #datasets and accelerate discoveries. At Genie TechBio Inc., we are leveraging these breakthroughs to empower biologists with AI-driven solutions for analyzing intricate #omics data. By integrating #machinelearning with #lifesciences, we enable researchers to unlock insights faster, transforming how data is interpreted and driving forward advancements in #biotech and #drugdiscovery. These #Nobel-winning contributions remind us how #AI, rooted in #physics, is reshaping the future of #science and innovation across disciplines. #NobelPrize #AI #MachineLearning #Biotech #GenieTechBio #NeuralNetworks #Innovation #Omics #AIinScience #DataAnalysis #FutureofBiotech

🧬  𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗶𝗻𝗴 𝗚𝗲𝗻𝗔𝗜 𝗳𝗼𝗿 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗥𝗡𝗔-𝘀𝗲𝗾 𝗗𝗮𝘁𝗮 𝗖𝗹𝗲𝗮𝗻𝗶𝗻𝗴: 𝗔 𝗚𝗮𝗺𝗲-𝗖𝗵𝗮𝗻𝗴𝗲𝗿 𝗳𝗼𝗿 𝗕𝗶𝗼𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀💡 One of the most critical and time-consuming steps in analyzing #RNA—seq data is #data #cleaning - identifying and removing noise, outliers, and inconsistencies that can obscure meaningful biological insights. By leveraging #LLMs and powerful machine learning algorithms, researchers can now: 🧹 Automate tedious #data #cleaning tasks, such as handling missing values, #normalizing datasets, and identifying low-quality reads. 🧬 Rapidly identify patterns or anomalies that would otherwise require manual exploration. ⏩ Save time and focus on high-value analyses like #gene #expression #profiling, #differential #expression, and #functional #annotation. At Genie TechBio Inc., we’re building an #AI #bioinformatician that allows biologists to interact with their #omics data in #natural #language—no coding required. Imagine describing your data issues, and the #AI takes care of #cleaning, #preparing, and even #pre-#processing it. Data cleaning, simplified! 🔍 Want to explore how #GenAI can help streamline your #RNA-seq workflows? Let’s chat! 🚀 #Bioinformatics #Genomics #GenAI #RNAseq #DataScience #AIforBiology #GenieTechBio #Biotech #AI

𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗼𝗳 𝗦𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝗕𝗶𝗼𝗹𝗼𝗴𝘆 𝘄𝗶𝘁𝗵 𝗢𝗺𝗶𝗰𝘀 🧬 #synbio is rapidly advancing the way we engineer living systems, enabling the creation of entirely new biological functions. From sustainable materials to engineered #microbes for #medicine, the possibilities are endless. Central to these breakthroughs is omics—a suite of technologies like #genomics, #transcriptomics, #proteomics, and #metabolomics that allow us to explore and manipulate biology at a massive scale. So, how does #omics fuel innovation in #synbio? Here are some key ways it’s making an impact: #Genomics helps researchers design and reprogram DNA sequences, creating customized biological functions in cells and microorganisms. #Proteomics is critical for mapping out protein interactions and pathways, ensuring that engineered organisms operate efficiently in bioproduction and therapeutic applications. #Transcriptomics enables precise monitoring and control of gene expression, helping optimize biological systems for desired outcomes. #Metabolomics reveals the intricate metabolic networks within cells, which is crucial for designing microbes capable of producing everything from biofuels to pharmaceuticals. These technologies allow synthetic biologists to fine-tune complex systems, accelerate strain optimization, and bring us closer to real-world applications in healthcare, industry, and sustainability. 🔬 As #synbio and #omics continue to evolve together, we’re seeing exciting progress in creating new tools and applications that could revolutionize industries. Check out some of the companies leading the charge in synthetic biology innovation: Ginkgo Bioworks, Inc. Viridos Arzeda AmyrisTwist Bioscience Inscripta, Inc. 🌍 The future of #SyntheticBiology and #Omics is filled with possibility, and we can't wait to see where these fields take us next!

🚀 𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗢𝗺𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 🚀 #Omics research—whether it’s #genomics, #transcriptomics, #proteomics, or #metabolomics — can feel like navigating a data jungle 🌿. But with #ChatGPT, you’ve got a smart guide by your side to make the journey easier and faster. Here’s how #ChatGPT can give your omics analysis a serious boost: 𝗦𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗬𝗼𝘂𝗿 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀: Need to design a workflow for #RNA-seq, #proteomics, or #metabolomics? Just ask! #ChatGPT can help you map out the key steps, saving you time and making sure you don’t miss a beat. 🧬 𝗗𝗲𝗰𝗼𝗱𝗲 𝗖𝗼𝗺𝗽𝗹𝗲𝘅 𝗣𝗮𝗽𝗲𝗿𝘀: Struggling with a dense #research paper? #ChatGPT simplifies it—breaking down key concepts, methods, and findings, so you can stay focused on the big picture. 🧠 𝗧𝗼𝗼𝗹 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻, 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱: With so many #bioinformatics tools available, it’s easy to feel overwhelmed. ChatGPT suggests the right tools for your specific analysis, like #DESeq2 for transcriptomics or #MetaboAnalyst for metabolomics. 🔬 𝗕𝗿𝗮𝗶𝗻𝘀𝘁𝗼𝗿𝗺 𝗛𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗲𝘀: Stuck on what your data might mean? ChatGPT can help you generate #hypotheses and suggest potential biological insights—like having a virtual research partner always ready to brainstorm with you!💡 𝗟𝗲𝗮𝗿𝗻 𝗡𝗲𝘄 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 𝗙𝗮𝘀𝘁𝗲𝗿: Whether you’re diving into #single-cell RNA-seq or exploring #CRISPR screening, ChatGPT can break it down for you in minutes, so you can apply the latest techniques with confidence. 🔥 💡 #AI + #Omics = #Innovation: While ChatGPT doesn’t replace specialized bioinformatics software, it’s an incredible tool for brainstorming, planning, and learning—helping you spend less time searching and more time discovering. 🚀 At Genie TechBio Inc., we're building AI tools that make omics analysis faster and easier for researchers—no coding required! Ready to unlock the power of your data? Let’s talk! 💬 #Omics #AIinResearch #GenieTechBio #Omics #AIinResearch #LLMs #Bioinformatics #Genomics #Proteomics #Transcriptomics #Metabolomics #AI

𝗛𝗼𝘄 𝗢𝗺𝗶𝗰𝘀 𝗶𝘀 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗢𝗿𝗴𝗮𝗻𝗼𝗶𝗱 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 🧬 #Organoids — tiny, lab-grown replicas of human #organs-are changing the way we study biology and disease. And at the heart of this revolution is #omics-a suite of cutting-edge technologies like #genomics, #transcriptomics, #proteomics, and #metabolomics. So, how is omics driving this transformation? Here's a glimpse: #𝗚𝗲𝗻𝗼𝗺𝗶𝗰𝘀 makes sure organoids are genetically stable, ensuring they mirror human tissues. #𝗧𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽𝘁𝗼𝗺𝗶𝗰𝘀 uncovers gene expression patterns to fine-tune their development. #𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗮𝗻𝗱 #𝗺𝗲𝘁𝗮𝗯𝗼𝗹𝗼𝗺𝗶𝗰𝘀 validate how these mini-organs behave at the protein and metabolic levels—key for testing new #drugs and #treatments. Together, omics and organoids are paving the way for breakthroughs in #drugdiscovery and #personalizedmedicine. 🌱 Check out these pioneers shaping the future of organoid research: Hubrecht Institute, Developmental Biology and Stem Cell Research, AxoSim, DefiniGEN, Organovo Holdings, Inc., Emulate, Inc., Biopredic International, 3Dnamics. 💡 We know we’ve only scratched the surface! If you’re part of an emerging company developing exciting #organoid technologies, tag yourself below and let us know what you’re working on. We’d love to hear about it! 👇