Adrian Benjamin’s Post

High-definition #spatialbiology data doesn't have to mean cumbersome analysis. #VisiumHD features user-friendly analysis and visualization pipelines that empower intuitive exploration of whole transcriptome spatial gene expression at single cell–scale resolution overlaid onto microscopy images. Dive into the complex cellular landscapes of human #FFPE #coloncancer, lung and spleen, or mouse intestine and brain with these new datasets: https://bit.ly/3VNH1fv

📍 Single-cell multiplex chromatin and RNA interactions in ageing human brain   Wen et al. introduced the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA-chromatin associations within individual nuclei.   Key points ☑ Delineating diverse cortical cell types and states ☑ Correlation of nuclei exhibiting fewer short-range chromatin interactions with an ‘older’ transcriptomic signature and Alzheimer’s disease ☑ Uncovering cellular heterogeneity in XIST-chromosome X association levels (XAL) within the female cortex ☑ Exploring the covariation between XAL and chromatin interactions among female cortical cells. ➡ More details: https://lnkd.in/ewB8uCSJ #UniversityofCaliforniaSanDiego #spatialomics #spatialbiology #singlecellanalysis #singlecell

Advancing Tissue Mapping with #Spapros🚀   A team led by Prof. Fabian Theis #HelmholtzMunich has developed Spapros, a computational pipeline transforming spatial #transcriptomics.   💡By optimizing gene selection and probe design, Spapros enhances our understanding of tissue organization and cellular diversity at single-cell resolution.   Why it matters: 🌟High-resolution mapping of cellular interactions 🌟Improved insights into tissue-specific gene expression 🌟Unlocking new potential for precision medicine 🌟Transforming spatial biology for the future of disease research and #therapy   👉Learn more in our news: https://lnkd.in/d8BwF2jB   Fabian Theis Malte Lücken Louis Kümmerle Institute of Lung Health and Immunity #SpatialBiology #ComputationalBiology #PrecisionMedicine #gene

Which protocol do you use for differentiation of #sensoryneurons from #iPSCs? Here, we tested two differentiation protocols (small molecule-Chambers and directed differentiation-Anatomic) using manual and high throughput patch-clamp, multi-electrode arrays, gene expression, and FLIPR. We show that the Anatomic protocol can be nicely used for disease modelling, e.g. for small fiber neuropathy (SFN) or erythromelalgia (IEM), similar to what is known for the Chambers protocol. See here for details: https://lnkd.in/e_n7rh3W Thank you for the fruitful cooperation: Dr. Anil Kalia Corinna Rösseler Rafael Granja-Vazquez @Ayesha Ahmad Joseph Pancrazio @Anika Neureiter @Mei Zhang Daniel Sauter, Ph.D. Irina Vetter Åsa Andersson Greg Dussor Ted Price Benedict Kolber Vincent Truong and Patrick Walsh.

Michelle Hung's talk on "Synthetic Biology Approaches to Improve Cell Therapy Function" was enlightening! Our Novel Gene Circuit Technology Platform allows us to engineer smarter medicines, addressing fundamental disease challenges in the clinic. Starting right the first time with GeneFab's Synthetic Biology Toolbox will save you time and ensure success along the clinical path. Come and stop by our booth if you are interested to learn more. #SyntheticBiology #CellTherapy #InnateKiller2024

We’re excited to see our client, bit.bio, highlighted in Inside Precision Medicine’s latest exploration of cell and gene therapy. This article dives into the revolutionary role of precision cell programming in advancing treatments, with bit.bio at the forefront of overcoming some of the biggest challenges in the field. It’s an honor to support bit.bio in their mission to transform healthcare through innovative science. Check out the full article here: https://lnkd.in/efNQijZZ #BitBio #PrecisionMedicine #CellTherapy #GeneTherapy #HealthcareInnovation #Biotech

📍 Inferring spatially informed transcription factor activity across cellular contexts Zhang et al. presented STAN, a linear mixed-effects computational method that predicts spot-specific transcription factor (TF) activities by integrating curated TF-target gene priors, mRNA expression, spatial coordinates, and morphological features. ➡️ More details: https://lnkd.in/e7AMsS9Z #UniversityofPittsburgh #spatialomics #spatialbiology #singlecellanalysis #singlecell

🎉 Exciting advancements in BMKGENE Spatial Transcriptomics! The combination of BMKMANU spatial transcriptomics chip and single-cell segmentation technology has yielded remarkable results in the analysis of mouse embryo head tissues. 🔬 By integrating fluorescence, H&E staining, and gene expression data into the same section, precise clustering has facilitated accurate retrospective visualization of tissue structure. This achievement has expanded the tissue experience of BMKGENE and demonstrated the excellence of this technology. 🔍 💡 We look forward to more customers knowing and using our technology. #biologicalresearch #spatialtranscriptomics #singlecellanalysis #BMKGENE

What separates ResolveDNA WGA from other whole genome amplification kits out there? Hear from Aleksei Mikhalchenko, PhD, Genome Informatics Lead at the Center for Embryonic Cell and Gene Therapy, Oregon Health & Science University ⤵   "Our research depends critically on the ability to sequence single-cell DNA and accurately identify its genomic variants. Among all the whole-genome amplification (WGA) methods we have tested, PTA-based WGA has provided the most accurate output. It reliably stays close to the original 50/50 ratio of allele frequency in heterozygous loci, minimizing allele dropout and false-positive loss of heterozygosity. This makes it an invaluable tool for our research." Don’t settle for whole genome amplification kits that make you choose between high fidelity, even, or complete coverage. Our novel PTA-powered ResolveDNA WGA kits provide all three. Learn more: https://lnkd.in/gm37WwEJ

Excited to announce that, following the publication of GeneRAIN (https://lnkd.in/dHRtmPjx), our latest work "Genes in Humans and Mice: Insights from Deep Learning of 777K Bulk Transcriptomes" is now available online! Leveraging vast datasets of 410K human and 366K mouse bulk RNA-seq samples, along with our powerful GeneRAIN model, we characterized and compared genes at the RNA level across species. Our findings help explain why many biomedical gene studies succeed in mice but fail in humans! This is just another application of GeneRAIN – there's so much more we can explore! Check out the paper (https://lnkd.in/dS4hckb3) and stay tuned for updates. Huge thanks to all the authors and my amazing supervisory team Emily Oates @Marcel Dinger and Fatemeh Vafaee for their invaluable contributions. #deeplearningai #bioinformatics #gpt #bert #rnaseq #transformer