NanoString Technologies, Inc.’s Post

#AACR24 Poster number 2! Come visit with me today (section 27, poster 5) and chat about “Exploring the potential of targeted DNA Nanobot delivery systems for gene delivery” DNA Nanobots

Want to know which genes in your scRNA-Seq data are differentially expressed across trajectory branches? Try our latest tool, 𝐬𝐜𝐌𝐚𝐒𝐢𝐠𝐏𝐫𝐨. 𝐬𝐜𝐌𝐚𝐒𝐢𝐠𝐏𝐫𝐨 is an R package that uses polynomial GLMs to model differential gene expression along Pseudotime, effectively helping you analyze single-cell trajectory branches. I am deeply grateful to my co-authors, Ana Conesa, María José Nueda, Stefan Götz, PhD, and Marta Benegas Coll, for their invaluable support in developing this tool. Read the full paper https://lnkd.in/dmv8WJDV. Explore the Package Vignettes at https://lnkd.in/dRgqP_99.

Scientists have developed a new red fluorescent tag for the C. elegans worm that glows much faster than previous versions. This will allow researchers to see rapid changes in gene expression during this tiny creature's development. Read more: https://oxford.ly/3Z6CzZw

MUSTANG is breaking new ground in spatial transcriptomics! This reference-free, multi-sample deconvolution tool deciphers complex cellular compositions while preserving spatial context, transforming our ability to analyze tissue-level gene expression. Learn more about the revolutionary tool developed to tackle a critical gap in spatial transcriptomics analysis in our blog: https://lnkd.in/eGVNjXuM #spatialtranscriptomics #bioinformatics #geneexpression

What if you could see inside tissues with unprecedented clarity? A new tool called, MUSTANG is making waves in spatial genomics research! This tool goes beyond single-cell analysis and helps the user explore multi-sample insights that were impossible months ago. #Deconvolution #Bioinformatics #ComputationalBiology #SpatialGenomics #BioinformaticServiceProvider

The Allen Cell Collection is a complete list of all the cell lines we’ve generated. It includes quality control data, gene editing methods, SOPs for the correct use of our cells, and more. Learn how to navigate this treasure trove of cell science.👇

Last year, Dr. Christina Theodoris et al. published a paper introducing #Geneformer: a transformer-based model for predicting gene network dynamics from #singlecell transcriptomic data. Recently, the lab made several significant updates to the model, improving its performance in a variety of contexts. Check out our updated blog to learn about these changes and how they impact this #foundationmodel! https://lnkd.in/erj99xAw #transcriptomics #networkbiology

Discover Spatial Gradient Screening, an algorithm that facilitates the supervised detection of histology-associated gene expression patterns without prior data grouping. 🖨️ This work was published in Nature Communications by Dr. Dieter Heiland and team. https://lnkd.in/gHT5C25W

🎤 Keynote 4 - DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements 🗣️ By: Luca Pinello 🌟 Come explore advancements at the intersection of Gene Expression and AI at #LatinXinAI #NeurIPS2024. 🚀

This article triggered my worst fear and highlights the importance of sequencing all your plasmids (shared by a lab/colleague or made by you) before doing anything with them. Sequencing is very affordable and is definitely worth it!