Pinned Tweet
🧪
We are excited to share our work on human blastoids as a model of pre- and peri-implantation human development (@leo_jwu, @hon_lab, @leqianyu, @Yyyyyy1005,@jlduan).
Article: dx.doi.org/10.1038/s41586-02… News and Views: doi.org/10.1038/d41586-021-0… (1/10)
Scientists flock to DeepSeek: how they’re using the blockbuster AI model nature.com/articles/d41586-0…
Jialei Duan retweeted
A community effort to optimize sequence-based deep learning models of gene regulation go.nature.com/3NnblYZ
Jialei Duan retweeted
FDA new drug approvals in Q3 2024
tinyurl.com/4axj5wbz
Several of the products approved in the the last quarter are expected to become blockbusters, including Cobenfy for schizophrenia, Kisunla for Alzheimer disease and Ebglysss for atopic dermatitis
Jialei Duan retweeted
Epigenome editing is transforming biological sciences and medicine. We're grateful for the opportunity to publish this review of the field in @NatureBiotech. Check it out here: rdcu.be/dPjsJ
Epigenome editing technologies for discovery and medicine go.nature.com/4cXw54M
Jialei Duan retweeted
Excited to share our pre-print, spearheaded by @DoronTheViking (who did a phenomenal job, great fun to have grad students come up with the best ideas) providing a way to integrate scRNA-seq and spatial transcriptomics that fully utilizes spatial context biorxiv.org/cgi/content/shor…
Jialei Duan retweeted
Zinc finger design is facilitated with a deep-learning model go.nature.com/3HBtUH5
Jialei Duan retweeted
Data sharing in the age of deep learning
How can we protect personal information and the integrity of artificial intelligence models when sharing data? go.nature.com/43ehqho
Jialei Duan retweeted
Excited to share our TRACERx nature publication on circulating tumor DNA (#ctDNA, #MRD) detection in resectable lung cancer led by @AbboshChris, @Afrankell, @juditkisistok, Thomas Harrison, Aaron Garnett, @nbirkbak and @NickyMcGranahan 👇👇👇 Tweetorial🧵
nature.com/articles/s41586-0…
Jialei Duan retweeted
Thrilled to share our new method, Nano-tRNAseq, a @nanopore direct #RNA sequencing approach that simultaneously quantifies tRNA abundances and modifications. If you’re interested in sequencing other small RNA types with nanopore, this method might interest you 1/ 🧵 – at Barcelona, Spain
Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing go.nature.com/3ZH3eu8
Jialei Duan retweeted
A relay velocity model infers cell-dependent RNA velocity go.nature.com/3GaKgFa
Jialei Duan retweeted
We are excited to introduce Phospho-seq, our approach for profiling intracellular protein and cell signaling dynamics alongside additional molecular modalities in single cells!
Check out @JBlairSci's preprint at biorxiv.org/content/10.1101/…
Jialei Duan retweeted
Replying to @TheCoxLab
@TheCoxLab and @Coon_Labs scientists succeeded in developing a new method to generate a more detailed #proteome than ever before, providing insights into how #GeneticVariants and #SpliceVariants in humans impact the proteome.
Published in @NatureBiotech
nature.com/articles/s41587-0…
Jialei Duan retweeted
A study in @NatMetabolism demonstrates that loss of PCYT2-synthesized phosphatidylethanolamines in muscle impairs sarcolemmal lipid bilayer stability and mitochondrial homeostasis, leading to muscle degeneration and premature ageing in mice. 🔒 go.nature.com/3JEyvHY
Strife at eLife: inside a journal’s quest to upend science publishing nature.com/articles/d41586-0…
Jialei Duan retweeted
Unveiled today at @nvidia's GTC- significant expansion of our #BioNemo cloud service for LLMs and Generative AI for Life Sciences R&D.
nvidianews.nvidia.com/news/n…
Honored to work with so many brilliant individuals and teams across Nvidia to build these technologies.
Inheritance of epigenetic DNA marks studied in new mouse model nature.com/articles/d41586-0…
Jialei Duan retweeted
New content online: High-throughput manufacturing of epitaxial membranes from a single wafer by 2D materials-based layer transfer process dlvr.it/SlC38k
Jialei Duan retweeted
Two new preprints for performing differential expression across conditions in scRNA-seq data, *without* having to call clusters first:
1. LEMUR (from @const_ae @wolfgangkhuber): biorxiv.org/content/10.1101/…
2. miloDE (from @Alsu_Troost @MarioniLab): biorxiv.org/content/10.1101/…
























