AI Tool Could Predict Single Cell RNA Sequencing and Expression

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scGPT - improves single cell RNA sequencing by predicting gene expression in individual cells, although it may be some time before it enters general use. </div> </div> <div class="header-graphic flex-1"> <img src="https://oxfordglobal.com/hubfs/Website/Images/Resources/Omics/AI-Tool-Could-Predict-Single-Cell-RNA-Sequencing-and-Expression.jpg" class="header-graphic-image"> </div> </div> </div> </div> <div class="container-wrapper"> <div class="wide-container"> <div class="content"> <div class="content-body text-gap"> <p>Single cell RNA sequencing (scRNA-seq) could be augmented by the integration of AI to improve scRNA-seq prediction of RNA transcripts.</p>   <p>While scRNA-seq as a sequencing approach enables the visualisation of differential gene expressions at a higher resolution, the approach can generate data with a degree of both variability and background noise.</p>   <p>Now, a new approach that pioneers the integration of machine learning tools to overcome these technical challenges is being introduced.</p>   <p>Bo Wang, a Computational Biologist at the University of Toronto, constructed a new artificial intelligence (AI) model with a team of computer scientists and cell biologists. </p>   <p>The AI model - a single-cell generative pretrained transformer (scGPT) - can be fine-tuned to run a diverse range of tasks and prompts using scRNA-seq data. </p>   <p>Wang explained in <em><a href="https://www.the-scientist.com/news/a-new-ai-tool-predicts-gene-expression-in-a-single-cell-71295" target="_blank" rel="noreferrer noopener">The Scientist</a></em> that the AI's core model could be built upon and tweaked into distinct versions that carry out a range of downstream tasks, predicting the expression levels of genes in a cell.</p>   <p>The model approach involved the construction of a single-cell foundation model through generative pre-training carried out on over 10 million cells. </p>   <p>By employing a single base model to perform many downstream tasks, scGPT avoids encountering issues associated with misalignment that can arise when multiple computational models are used to carry out different tasks. </p>   <h2 id="h-augmenting-single-cell-rna-sequencing-with-machine-learning"><strong>Augmenting Single Cell RNA Sequencing with Machine Learning</strong></h2>   <p>In recent years, scRNA-seq technology has become the state-of-the-art approach for interpreting the heterogeneity and complexity of RNA transcripts within individualised cells.</p>   <p>The approach reveals the composition of different cell types, placing more emphasis on measuring the genomes of individual cells from a given population. </p>   <p>Through measuring the RNA molecules within each cell of a given sample, scRNA-seq provides a snapshot of the transcriptome when the cells were harvested. </p> <p><strong>RELATED:</strong></p>   <ul> <li><a href="https://oxfordglobal.com/omics/resources/navigating-post-translational-modifications-in-single-cell-analysis/" target="_blank" rel="noreferrer noopener">Highlights from NextGen Omics UK: Post-translational modifications in single cell analysis</a></li>   <li><a href="https://oxfordglobal.com/omics/resources/current-bioinformatics-trends-in-single-cell-data-analysis-good-practice-makes-perfect/" target="_blank" rel="noreferrer noopener">Current bioinformatics trends surrounding single cell data analysis</a></li>   <li><a href="https://oxfordglobal.com/omics/resources/utilising-single-cell-metabolomics-to-reveal-metabolic-cell-states/" target="_blank" rel="noreferrer noopener">Revealing cellular state with single cell metabolomics</a></li> </ul>   <p>Although the findings from the University of Toronto have huge potential, there are considerations that should be taken into account before the approach is unilaterally introduced. </p>   <p>For one, the models contain millions of parameters and require a huge volume of data to train: this means they consume a lot of energy, leaving a significant carbon footprint. </p>   <p>Researchers involved in using the technology will also require a degree of familiarity with machine learning, leaving some ambiguity as to how widely scGPT could be adopted among cell biologists. </p>   <p>Since its development, scRNA-seq has found a large number of applications. </p>   <p>Although the final product of a gene's expression is its protein, detecting its messenger RNA indicates the gene is turned on and, therefore, has the potential to be subsequently translated and expressed. </p>   <p><em>Get your regular dose of industry news and announcements </em><a href="https://oxfordglobal.com/omics/news/" target="_blank" rel="noreferrer noopener"><em>here</em></a><em>, or head over to our </em><a href="https://oxfordglobal.com/omics/" target="_blank" rel="noreferrer noopener"><em>Omics portal</em></a><em> to catch up with the latest advances in tumour analysis. To learn more about our upcoming NextGen Omics UK conference in London, </em><a href="https://oxfordglobal.com/nextgen-omics-series-uk/" target="_blank" rel="noreferrer noopener"><em>click here</em></a><em> to download an agenda or register your interest.</em></p>  <div class="content-body-footer"> </div> </div> <div class="content-sidebar"> <div class="related-articles"> <h3 class="center">Related Resources</h3> <div class="article"> <a href="/precision-medicine/resources/single-cell-tcrαβ-and-tcrγδ-immune-receptor-profiling-and-immunophenotyping-using-a-96-well-plate-sorted-cell-approach"> <div class="cover-graphic"> <img src="https://oxfordglobal.com/hubfs/Website/Documents/Whitepaper%20Upload%2022.10.24/04_2024_AACR-Single_Cell-TCR_11x17.jpg" class="cover-graphic-image"> </div> </a><div class="content"><a href="/precision-medicine/resources/single-cell-tcrαβ-and-tcrγδ-immune-receptor-profiling-and-immunophenotyping-using-a-96-well-plate-sorted-cell-approach"> <h4> Single-cell TCRα/β and TCRγ/δ immune receptor profiling and immunophenotyping using a 96-well plate sorted-cell approach </h4> <div class="abstract"> </div> <div class="read-more"> <a href="/precision-medicine/resources/single-cell-tcrαβ-and-tcrγδ-immune-receptor-profiling-and-immunophenotyping-using-a-96-well-plate-sorted-cell-approach" class="read-more-link">Read More</a> </div></a> </div> </div> <div class="article"> <a href="/precision-medicine/resources/exploiting-the-spatial-dimension-the-power-of-single-cell-spatial-transcriptomics"> <div class="cover-graphic"> <img src="https://oxfordglobal.com/hubfs/Website/Documents/Whitepaper%20Upload%2022.10.24/Spatial%20transcriptomics%20poster.jpg" class="cover-graphic-image"> </div> </a><div class="content"><a href="/precision-medicine/resources/exploiting-the-spatial-dimension-the-power-of-single-cell-spatial-transcriptomics"> <h4> Exploiting the spatial dimension: The power of single cell spatial transcriptomics </h4> <div class="abstract"> </div> <div class="read-more"> <a href="/precision-medicine/resources/exploiting-the-spatial-dimension-the-power-of-single-cell-spatial-transcriptomics" class="read-more-link">Read More</a> </div></a> </div> </div> </div> </div> </div> </div> </div> </div> <div class="newsletter-cta"> <h2 class="heading">Subscribe to our newsletter</h2> <div class="message"> Sign up for our monthly Newsletter to keep up with all things Precision Medicine </div> <div class="button-wrapper"> <a href="#" class="button hs-cta-trigger-button hs-cta-trigger-button-177053686110">Newsletter Sign-Up</a> </div> </div> </main> <div data-global-resource-path="git/og-stage/templates/partials/footer.html"><footer class="website-footer flex flex-column g-20"> <div class="footer-columns"> <div class="footer-column"> <a href="https://oxfordglobal.com" class="site-logo-link"> <img src="https://oxfordglobal.com/wp-content/uploads/2023/03/Oxford-Global-Logo-Stacked-Websize.png" class="site-logo"> </a> </div> <div class="footer-column"> <h3>Brands</h3> <ul> <li> <a href="/precision-medicine/">Precision Medicine</a> </li> <li> <a href="/discovery-development/">Discovery & Development</a> </li> <li> <a href="/nextgen-biomed/">NextGen Biomed</a> </li> </ul> </div> <div class="footer-column"> <h3>Services</h3> <ul> <li> <a href="https://oxfordglobal.com/in-person-services/"> In-Person Services </a> </li> <li> <a href="https://oxfordglobal.com/digital-marketing-services/"> Digital Marketing Services </a> </li> </ul> <h3>Upcoming Events</h3> <ul> <li> <a href="https://oxfordglobal.com/calendar/"> Event Calendar </a> </li> </ul> </div> <div class="footer-column"> <h3>Company</h3> <ul> <li class="elementor-icon-list-item"> <a href="https://oxfordglobal.com/about-us/"> About </a> </li> <li class="elementor-icon-list-item"> <a href="https://oxfordglobal.com/vacancies/"> Vacancies </a> </li> <li class="elementor-icon-list-item"> <a href="https://oxfordglobal.com/csr-policy/"> CSR Policy </a> </li> <li class="elementor-icon-list-item"> <a href="javascript:postMessage({type:'HS_DISPLAY_CALL_TO_ACTION',id:130207947529});"> Contact </a> </li> </ul> </div> <div class="footer-column"> <p> <a href="tel:+441865248455">+44 1865 248 455</a><br> <a href="mailto:help@oxfordglobal.com">help@oxfordglobal.com</a> </p> <p> <strong>Our UK Address:</strong><br> Godstow Court<br> Minns Business Park<br> Botley<br> Oxford, OX2 0JB </p> <p> <strong>Our US Address:</strong><br> 100 Cambridge Street<br> 14th Floor<br> Boston<br> MA 02114 </p> </div> </div> <div class="footer-bottom grid g-20"> <div class="span8 span12-sm span12-md flex flex-column g-10"> <div class="copyright"> © Oxford Global Marketing Ltd. 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AI Tool Could Predict Single Cell RNA Sequencing and Expression