Gerstein Lab | Yale

New study conducted by our lab in collaboration with #PsychENCODE has made significant discoveries linking genetic variants to genes and cell types in human brain. #psychencode24 For more details, refer to our original thread: x.com/MarkGerstein/s… news.yale.edu/2024/05/23/tra…

🔐 New open-access paper in Cell Reports Methods! We show that fully homomorphic encryption enables privacy-preserving polygenic risk scores (PRS), allowing secure computation directly on encrypted genomes with near-zero accuracy loss. 📄 cell.com/cell-reports-m…

🚀 New paper in Bioinformatics! Our #ASTRO work led by @dingyao_zhang introduces "ASTRO: Automated Spatial-Transcriptome whole RNA Output", an automated pipeline optimized for whole-transcriptome spatial analysis, especially in challenging FFPE samples. 🔗 doi.org/10.1093/bioinf…

@NeurIPSConf @_YunyangLI This work is a close collaboration with colleagues previously at Microsoft Research (@MSFTResearch) and currently at Ubiquant and various other places. Huge thanks to them for the ideas and computational resources.

Our @NeurIPSConf work led by @_YunyangLI “E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products” was selected as a spotlight (with score ranked ~17 / 21k submissions). Poster: Thur Dec 4, Exhibit Hall CDE #5512 Online: openreview.net/forum?id=ls5L4…

By @RanMeng_m, William Zhu, Christopher Cameron, Pengyu Ni, Xiao Zhou, Tselmeg Ulammandakh, and @MarkGerstein.

🆕Our new PNAS study bridges histology and genomics! Using deep learning and imageQTL analysis, we show how tissue images reflect gene expression and aging — making histology more interpretable with AI. pnas.org/doi/10.1073/pn…

By @RanMeng_m, William Zhu, Christopher Cameron, Pengyu Ni, Xiao Zhou, Tselmeg Ulammandakh, and @MarkGerstein.

📚 Yale students have returned to campus, so time for a roster meeting! We again made our Nobel Prize predictions (given how accurate we were last year 😉) 🥇Our top prediction is Habener & Knudsen (GLP-1) with 28.5% of the vote! 🥈 In second is Rothberg & David Klenerman (NGS)

New @NatureComms paper led by @beaborsari & Mor Frank. Also thanks to co-authors Eve Wattenberg, @KeXU0828, @Susannaliu99, @XuezhuYu & @MarkGerstein!

Curious how your favorite gene changes when and how during a biological process? Want to dive into the kinetics of chromatin + gene expression? Meet chronODE, our new tool to model multi-omic time-series with logistic equations + ML! doi.org/10.1038/s41467…

3/3 The test yielded a p-value of 4.91 × 10⁻⁸, which is far below the conventional significance threshold of 0.05. This indicates a statistically significant deviation in personality type distribution within the lab.

2/3 In contrast, within the Gerstein Lab, there are 26 Analysts, 20 Diplomats, 6 Sentinels, and 4 Explorers. A chi-square goodness-of-fit test was conducted to evaluate whether the MBTI distribution in the lab significantly differs from that of the general population.

🧠 At our recent Gerstein Lab roster meeting, we took a detour into… personality science! Turns out we’re INT Central 🧪 📌 70% Introverts 📌 83% Intuitives 📌 57% Thinkers Analysts (INTP, INTJ) dominate, far more than the U.S. baseline. #MBTI #INTP #INTJ

@_YunyangLI @MarkGerstein @MSFTResearch You can read more here: openreview.net/forum?id=twEvv…

@_YunyangLI @MarkGerstein @MSFTResearch 4/4 ⚡ WANet + WALoss ⇒ 18 % faster SCF convergence & 1 000 × energy-error reduction vs. SOTA. One model, many properties—HOMO/LUMO, dipoles, electron densities—all from a single predicted Hamiltonian.

1/4 🚀 New #ICLR2025 SPOTLIGHT ALERT Gerstein Lab presents “Enhancing the Scalability & Applicability of Kohn-Sham Hamiltonians”—led by  @_YunyangLI & Z Xia & L Huang & J Zhang & @MarkGerstein. Joint work with @MSFTResearch.

Our new paper in @jbi_journal describes the iDASH-winning method for efficient blockchain storage of biomedical data. We cut gas costs by 60% and sped up retrieval 500x with low-level Solidity optimization. By Eric Ni, Elizabeth Knight, @MarkGerstein doi.org/10.1016/j.jbi.…