Xiaowei Zhang (@xiaowei0402) 's Twitter Profile
Xiaowei Zhang

@xiaowei0402

ID: 1488677400632168448

calendar_today02-02-2022 00:55:33

7 Tweet

21 Followers

43 Following

Jingjia Liu (@ljjchem) 's Twitter Profile Photo

It has been a great pleasure working on this project in which the the initial idea came from creative insights on a protein structure. Huge thanks to Haotian Du, Possu and everyone❤️❤️❤️

Xiaowei Zhang (@xiaowei0402) 's Twitter Profile Photo

Super excited to share our work on post-transcriptional synthetic receptors, and really looking forward to see LIDAR to be a helpful tool to the field of SynBio! Huge thanks to all the authors!!!

Xiaojing Gao (@synbiogaolab) 's Twitter Profile Photo

LIDAR is out! rdcu.be/efugD We've improved a lot, e.g., making MESA-like LIDAR work, RNAseq of on-/off-target editing, and optimizing RNA delivery. We are one baby step closer to making it useful for therapeutics. NIH high-risk high-reward program provides key support.

Stanford Bio-X (@stanfordbiox) 's Twitter Profile Photo

2 new papers from Dr. Xiaojing Gao Xiaojing Gao with Bio-X Fellows Carlos Aldrete , Santiago Mille , and Eerik Kaseniit , with support from Stanford Bio-X Seed Grants, introduce revolutionary new protein and RNA editing platforms for cell-based therapy! biox.stanford.edu/highlight/new-…

Xiaowei Zhang (@xiaowei0402) 's Twitter Profile Photo

Super excited — We hope this new modular post-transcriptional synthetic receptor platform will further broaden the horizon of RNA compatible therapies! Huge thanks to everyone on LIDAR, especially Xiaojing who enabled the whole story & fantastic collaboration with Santiago Mille

Xiaojing Gao (@synbiogaolab) 's Twitter Profile Photo

Have you always wanted to take a protein from its native context and make it work elsewhere? Our novel sampler computationally “cytosolize” a secreted enzyme while maintaining its structure, generalizable to other multi-objective guided generation tasks biorxiv.org/content/10.110…

Santiago Mille (@santimillef) 's Twitter Profile Photo

The ability to design antibodies against any protein of interest has major implications for medicine, biotech, and basic science. Today, we introduce Germinal, a pipeline for epitope-targeted de novo antibody design achieving  4–22% success rates with efficient experimental

The ability to design antibodies against any protein of interest has major implications for medicine, biotech, and basic science. 

Today, we introduce Germinal, a pipeline for epitope-targeted de novo antibody design achieving  4–22% success rates with efficient experimental