Assistant Professor @ Stanford ChemE synthetic biology, biomolecular engineering https://xitter.cf/t.co/KAajKt7YdT
Stanford, CA
Joined June 2019
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Numerous biotech innovations started with adapting a protein to its non-native context, which often requires substantial experimental optimizations. Here’s a breakdown by our lead, @Xiaowei0402, on a versatile, efficient computational framework to facilitate such adaptations.
Xiaojing Gao retweeted
Regulatable in vivo gene expression via adaptamers sciencedirect.com/science/ar…
Laura Yang and @BingfeiY for guiding us through ESCAPE-seq so that we can collect an experimental proxy for HLA-I binding, and Elena Sotillo and Kevin Reynolds from the Mackall lab for CAR function validation.
Xiaowei is the mastermind, also with contributions from current and former lab members @ sophiaburick, @haoyu_dai_dhy, @Geonhu_Lee, Zi Liu, and @santimillef. Read here: doi.org/10.1101/2025.07.11.6…
Congrats, Brian and team. It never ceases to amaze me what you guys can do with the language models!
As with biological design, AI can also accelerate biological discovery.
In new work led by @_David_Li and @garykbrixi with @mfgrp, we show how genome language models enable systematic discovery of genetic elements, revealing a new class of reverse-transcriptase mechanisms.
Xiaojing Gao retweeted
As with biological design, AI can also accelerate biological discovery.
In new work led by @_David_Li and @garykbrixi with @mfgrp, we show how genome language models enable systematic discovery of genetic elements, revealing a new class of reverse-transcriptase mechanisms.
Heading to mSBW? Check out work by @cnnrcall (Poster 47, genetically encoded urinary reporter to noninvasively monitor live molecular events), JS (Poster 46, efficient biophysical design of orthogonal DNA duplex libraries), and @mengzhang668 (talk, ablating cancer using RADAR).
Please RT: We're hiring! Computational postdoc for foundation model and sequence-structure-function studies of intrinsic disordered proteins through a consortium and unique large datasets. Ideal candidates have led ML/AI projects in protein design/analysis.
Xiaojing Gao retweeted
Efficient generation of epitope-targeted antibodies with Germinal - @BrianHie @SynBioGaoLab nature.com/articles/s41587-0…
Stop by our posters at SEED! @haoyu_dai_dhy on our latest efforts to improve ADAR-based sensors (Day 1, #24), @FloraHU8 on their application to cancer ablation (Day 1, #23), and @Xiaowei0402 on an efficient algorithm to refactor proteins for biomedical applications (Day 2, #136).
Xiaojing Gao retweeted
Nifty work on plasmid chromatinization from @stergachislab !
"plasmids are indeed capable of recapitulating nuclear genome-encoded chromatin architectures, ... However, plasmids consistently adopt a heterogeneous and incomplete chromatin architecture relative to nuclear-encoded chromatin fibers, and surrounding sequence context plays an integral role in modulating whether a plasmid-encoded regulatory element will recapitulate nuclear genome-encoded chromatin architectures."
Online Now: Chromatin architectures underlying plasmid-based assays for regulatory variant effects dlvr.it/TSkLhj
Xiaojing Gao retweeted
I have long written and spoken about the many ways US immigration policy harms international students and scholars. This has been true for as long as I can remember, including when I first came to the US on a single-entry student visa more than 20 years ago under a process formerly known as muslim registry program.
But the current administration has gone much further, through arbitrary policy changes, travel bans, and broad visa processing pauses that leave folks unable to work, travel, or train.
These policies affect a minority of scientists, and in the current state of the world they can be easy to overlook. But we should not let that happen.
I wrote about the quiet loss of Iranian scientific talent in US labs for @TheScientistLLC:
the-scientist.com/the-quiet-…
Xiaojing Gao retweeted
qPCR allowed us to measure transcripts, but just once, destructively, and only in post-mortem tissues. Here, we show we can record transcript level history in vivo and recover this information with a blood test to make a "noninvasive qPCR". nature.com/articles/s41467-0…
Xiaojing Gao retweeted
1/ Excited to share our new paper in Science: “Toward life with a 19-amino acid alphabet through generative artificial intelligence design.” @ColumbiaSysBio @ColumbiaBME @Columbia
science.org/doi/10.1126/scie… 🦠🧬🛠️🖥️💥
