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Dr Pushmita Kohli is one of the most outstanding scientists in the world today. Fascinating to get to know what he has to say. #artificialintelligence #ai #machinelearning #ml #biotech #pharma #medicalscience #materialscience #future #google #deepmind

🧬🔍 𝗗𝗲𝗰𝗼𝗱𝗶𝗻𝗴 𝗚𝗲𝗻𝗲𝘁𝗶𝗰 𝗠𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝘄𝗶𝘁𝗵 𝗔𝗜: Google DeepMind's groundbreaking research unveils a new AI tool that classifies the effects of 71 million 'missense' mutations, offering a clearer understanding of potential disease-causing genetic changes. Key insights: 1️⃣ 𝗠𝗶𝘀𝘀𝗲𝗻𝘀𝗲 𝗩𝗮𝗿𝗶𝗮𝗻𝘁𝘀: Genetic mutations that can influence human protein functions, potentially leading to diseases like cystic fibrosis and cancer. 2️⃣ 𝗔𝗹𝗽𝗵𝗮𝗠𝗶𝘀𝘀𝗲𝗻𝘀𝗲 𝗖𝗮𝘁𝗮𝗹𝗼𝗴𝘂𝗲: Developed using the AlphaMissense AI model, this catalogue classifies 89% of all possible missense variants, a significant leap from the 0.1% confirmed by human experts. 3️⃣ 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵: AI predictions can preview results for thousands of proteins simultaneously, streamlining resources and fast-tracking intricate studies. 4️⃣ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲: DeepMind has made AlphaMissense's predictions freely available to the scientific community, furthering global understanding of proteins. 5️⃣ 𝗥𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗜𝗺𝗽𝗮𝗰𝘁: Collaborations with Genomics England confirm the accuracy of AlphaMissense's predictions, highlighting its potential in diagnosing rare genetic disorders and aiding in the discovery of new disease-causing genes. 🌐 Dive deeper into this transformative research and explore the potential of AI in genomics. Unlock the future of genetic disease research and treatment! 👉 Read more: https://lnkd.in/gYpskA5t #DeepMind #Genomics #AIResearch #MissenseVariants #AlphaMissense #GeneticDiseases #InnovativeTechnology

The article titled "A catalogue of genetic mutations to help pinpoint the cause of diseases" discusses the development of an AI tool called AlphaMissense by DeepMind. This tool classifies the effects of 71 million ‘missense’ mutations. Missense variants are genetic mutations that can affect the function of human proteins and potentially lead to diseases such as cystic fibrosis, sickle-cell anemia, or cancer. The AlphaMissense tool categorizes these missense variants as either likely pathogenic or likely benign. In a paper published in Science, it is reported that AlphaMissense classified 89% of all 71 million possible missense variants. This is a significant advancement considering that only 0.1% of these variants have been confirmed by human experts. AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics. By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritise resources and accelerate more complex studies. The predictions made by AlphaMissense can help accelerate research in various fields, including molecular biology, clinical genetics, and statistical genetics. AlphaMissense is based on our breakthrough model AlphaFold, which predicted structures for nearly all proteins known to science from their amino acid sequences. Our adapted model can predict the pathogenicity of missense variants altering individual amino acids of proteins. DeepMind has made all predictions freely available to the research community and open-sourced the model code for AlphaMissense. This initiative aims to facilitate faster diagnosis and the development of life-saving treatments by uncovering the root causes of diseases. AlphaMissense outperforms other computational methods on predicting missense variant effects. Please note that this summary is based on my understanding of the article and may not include all details. For more information, I recommend reading the original article here. One thing is clear we are heading towards a very exciting time on new Innovation and exploring a bright future. Google Google DeepMind #Google #DeepMind #AI #AlphaMissense #MolecularBiology #ClinicalGenetics #StatisticalGenetics #Pathogenic #HumanGenetics #Cancer #MolecularBiology #AlphaFold #GoogleBard #GoogleCloud #BardAI #ClinicalTrial #OpenSource

DeepMind's latest breakthrough, AlphaMissense, is transforming the field of genetic research. This cutting-edge model categorizes missense mutations, providing crucial insights into the impact of genetic alterations on proteins. With the ability to attribute likelihood scores for pathogenic or benign mutations, AlphaMissense is revolutionizing the identification of rare genetic diseases. Released last year, the algorithm has already classified approximately 89% of all possible human missense variants, marking a significant advancement in genetic data analysis. Previously, researchers had only clinically classified 0.1% of all possible variants, underscoring the transformative potential of AlphaMissense in genetic research and disease discovery. Read more about this groundbreaking innovation here: https://lnkd.in/dk-Y7qXq

"Machine learning is now helping researchers analyze the makeup of unfamiliar cells, which could lead to more personalized medicine in the treatment of cancer and other serious diseases. Researchers at the University of Waterloo developed GraphNovo, a new program that provides a more accurate understanding of the peptide sequences in cells. Peptides are chains of amino acids within cells and are building blocks as important and unique as DNA or RNA." #ai #peptides

Super excited that Google DeepMind launched AlphaMissense yesterday, a new AI tool that classifies the effects of 71 million missense mutations (genetic changes) - one step closer to discovering the causes of so many diseases including cancer. Some fun facts... ➡ The average person has over 9,000 missense variants - most benign but just one can be the cause of a disease. ➡ The AlphaMissense AI model categorised 89% of all 71 million possible missense variants as either likely pathogenic or likely benign. By contrast, only 0.1% have been confirmed by human experts. ➡ All AlphaMissense predictions are freely available to the research community via a catalogue with European Bioinformatics Institute | EMBL-EBI. Read our AlphaMissense blog! https://lnkd.in/eKKnVhR3 Or bbc: https://lnkd.in/euT-JyX2 FT: https://lnkd.in/ekUdfHer Super exciting development in the world of #aiforhealthcare. A recent study by Morgan Stanley said that AI could cut pre-clinical development costs by up to two fifths - potentially creating a $50bn market over the next decade. 📉

#BiotechDiaries AI algorithms are reshaping the medical management of liver disease, heart disease, Alzheimer’s disease, and various types of cancers by predicting disease risk and formulating personalised treatment plans. AI can analyse large datasets, of, e.g, demographic and regional information, to discover patterns and correlations that traditional diagnostic methods may miss. ✅ Research presented at the American Heart Association’s Scientific Sessions shows that AI can be harnessed to predict the risk of cardiac events over a 10-year period. The tool uses information on changes in arterial width and fat accumulation around inflamed arteries, among other clinical risk variables. ✅ The PRISM AI system uses massive datasets, created with information from millions of patients, to help identify those at risk of developing the most common form of pancreatic cancer, pancreatic ductal adenocarcinoma. ✅ Researchers at Google DeepMind have devised a tool, AlphaMissense, to predict the occurrence of harmful genetic mutations. The tool reviewed 71M so-called “missense” mutations, which impacts a single letter of the genetic code and was able to predict 89% of such mutations, with 90% accuracy. If you’re a startup looking to transform life sciences by leveraging the innovative potential of AI, reach out to us at www.bioangels.vc/contact/. Let’s explore how we can combine our strengths to bring about change. #BioAngels #AIinLifeSciences #AIinDiseasePrediction #AIinDiseasePrevention

Google DeepMind's new AI tool, #AlphaMissense, is a major breakthrough for biology research. It can uncover disease-causing mutations, which is a critical step in understanding and treating diseases. Genes are like the blueprints for life, and mutations can be thought of as typos in the code. Some of these typos are harmless, but others can disrupt the gene's function and cause disease. Finding harmful mutations is essential for diagnosing diseases and developing new drugs. Traditionally, scientists have used laboratory experiments to test the effects of mutations. However, this process can be time-consuming and expensive. AlphaMissense has been shown to be highly accurate, with over 90% accuracy in predicting the effects of mutations. It has also outperformed other computational methods in classifying variants from #ClinVar (https://lnkd.in/g5S_ktqq), a public database of known genetic variants. Google DeepMind's decision to share this tool for free is a huge favor to the biology community. https://lnkd.in/gVSU3Vw9?

This gene researcher is reshaping the genre. 🧬 As a bioinformatics research scientist, Dr. Natalie Twine's pioneering research is focused on uncovering the genetic basis of diseases such as Alzheimer’s disease. Alzheimer's and similar diseases involve multiple gene mutations. The interaction of these various mutations makes it difficult to pinpoint a single cause or target for treatment. Natalie and her team build cutting-edge tools using cloud computing and machine learning, using AI to sift through genomic data in search of patterns. They're paving the way for early detection, targeted treatments, and a future of personalised healthcare. Learn about Natalie's work unveiling the secrets of common diseases. 👇

AI Model Uses Genetic Information To Predict Risk of Developing Alzheimer’s Disease An international research team led by the Hong Kong University of Science and Technology (HKUST) has developed an artificial intelligence (AI)--based model that uses genetic information to predict an individual’s risk of developing Alzheimer’s disease (AD) well before symptoms occur. This groundbreaking study paves the way for using deep learning methods to predict the risks of diseases and uncover their molecular mechanisms; this could revolutionize the diagnosis of, interventions for, and clinical research on AD and other common diseases such as cardiovascular diseases. https://lnkd.in/gqnHWcmz