Kamyar Keshavarz

Insanely cool paper! @ketanpatelimmo1

Read more about our work in neuroscience on recent paper: CRISPR-TO a programmable tool to reorganize the transcriptome Paper: nature.com/articles/s4158… @StanfordBrain

In 1999, Tom Maniatis discovered something remarkable: neurons achieve self-avoidance via stochastic methylation of the protocadherin gene cluster. We've just discovered this locus is an evolvable in-vivo barcode across the human tissues: biorxiv.org/cgi/content/sh… 🧵

Best wishes for 2026 from our Lab at ebrahimkhanilab.bio We look forward to a year defined by discovery, curiosity, and bold exploration. Stay tuned for more news coming soon! #organogenesis #stemcellmodels #syntheticbiology #howtissuesarebuilt

Excited to present the first major work after starting our lab at Stanford and the Arc this year: CRISPR-All, a unified genetic perturbation language for programming any major type of genetic perturbation simultaneously, in any combination, at genome scale, in human cells.

Today in @Nature, in work led by @aditimerch, we report the ability to prompt Evo to generate functional de novo genes. You shall know a gene by the company it keeps! 1/n

CD43, but not CD41 or GPI-80, marks first definitive haematopoietic stem cells in the human embryo journals.biologists.com/dev/article/do…

1/ Excited to share our new study with @Brumbaugh_JB, now out in @NatureBiotech! P-bodies selectively sequester RNAs encoding cell fate regulators, often from the preceding developmental stage. Releasing these RNAs can drive changes in cell identity. 🧵nature.com/articles/s4158…

Excited to announce mBER, our fully open AI tool for de novo design of epitope-specific antibodies. To validate, we ran the largest de novo antibody experiment to date: >1M designs tested against 145 targets, measuring >100M interactions. We found specific binders for nearly half the targets, with up to 40% hit rates. Thread below:

Absolutely thrilled to share with you the final version of EPIclone, out now (open access) in @Nature. This has been an amazing collaboration with the lab of Lars Velten (@larsplus) at @CRGenomica nature.com/articles/s4158…

In this Review, @BernaSozen_ , Patrick Tam and @martinperaJAX summarize how recent studies of embryo models have advanced our understanding of cell state transitions of the pluripotent human epiblast and highlights some key remaining questions: doi.org/10.1242/dev.20…

🔥New Night Science paper!! Discovery happens when your initial plans fall apart but it requires you to have a particular mindset: it's not extraverted, orderly, neurotic or agreeable that's the most important – discovery requires an OPENNESS to new ideas and unexpected insights.

I love Church's and Langer's approach to running their research programs. Unfortunately, today's academic research culture is not very conducive to developing this type of environment. Thinking about ways of circumventing such obstacles... genengnews.com/topics/drug-di…

Very nice focus issue @CurrentBiology on Physics and Biology. cell.com/current-biolog… Some of us wrote a perspective article on "Where physics and biology meet" led by @WallaceUcsf and Deborah Taylor. cell.com/current-biolog…

Best practices for data visualisation:

The prominent role of the gut microbiome in modulating response to stress and circadian rhythm cell.com/cell-metabolis… @Cell_Metabolism open-access, by @jfcryan @gabriel_tofani @UCC and colleagues

BREAKING NEWS The 2024 #NobelPrize in Physiology or Medicine has been awarded to Victor Ambros and Gary Ruvkun for the discovery of microRNA and its role in post-transcriptional gene regulation.

Alfonso Martinez Arias @AMartinezArias starts the first half of the last afternoon session Alfonso exploits the properties of stem cells to study the genesis of systems that lead and sustain patterns, forms and functions of embryonic processes #Fig1" target="_blank" rel="nofollow noopener">nature.com/articles/s4158… The data from gastruloids suggest that the frog organizer may have been split into two in mammals #spemannmangold2024 @UniFreiburg @UPFBarcelona

Thrilled to share our „PRedictor Of PHEnoTypes“ model Prophet! Led by @Alejandro__TL & @_yji_, Prophet is a transformer-based model that predicts outcomes for unseen experiments. It aims to understands biology by learning across assays and phenotypes over 4.7M+ experiments.

Just as sci-fi heroes enter stasis for space travel, embryos can pause their development in a state of dormancy. We present the single-cell atlas of embryo dormancy revealing its dynamics & the role of the microenvironment. Congrats to Rui Chen & the team! doi.org/10.1016/j.stem…