Single-cell transcriptomics offers the promise of measuring the diversity of cellular phenotypes across species and diseases. Here, we present Stack, a foundation model trained on 149 million uniformly preprocessed human single cells that leverages tabular attention to generate representations for each cell informed by the cells in its context.
Generative genomic models can design increasingly complex biological systems. However, controlling these models to generate novel sequences with desired functions remains challenging. Here, we show that Evo can leverage genomic context to perform function-guided design that accesses novel regions of sequence space.
Large serine recombinases can mediate direct, site-specific genomic integration of multi-kilobase DNA sequences without a pre-installed landing pad, albeit with low insertion rates and high off-target activity. Here we present an engineering roadmap for jointly optimizing their DNA recombination efficiency and specificity.
The androgen receptor is a critical driver of prostate cancer. Here, to study regulators of AR protein levels and oncogenic activity, we developed a live-cell quantitative endogenous AR fluorescent reporter. Leveraging this AR reporter, we performed genome-scale CRISPRi screens to systematically identify genes that modulate AR protein levels.
Single-cell RNA sequencing has transformed cell biology by enabling precise transcriptomic measurements of individual cells. Here, we introduce scBaseCount, a single-cell RNA sequencing database that leverages an AI agent to automate discovery and metadata extraction, and standardize data processing.
Here, we introduce the EnCodon model series within CodonFM, a family of large foundation models trained on more than 130 million coding sequences spanning over 22,000 species, designed to learn the contextual grammar of codon usage directly from sequence.
Here, we develop an all-RNA platform for efficient, durable and multiplexed epigenetic programming in primary human T cells, stably turning endogenous genes off or on using CRISPRoff and CRISPRon epigenetic editors. We achieve epigenetic programming of targeted genomic elements without the need for sustained expression of CRISPR systems.
Bridge recombinases are naturally occurring RNA-guided DNA recombinases that we previously demonstrated can programmably insert, excise, and invert DNA in vitro and in Escherichia coli. In this study, we report the discovery and engineering of the bridge recombinase ortholog ISCro4 for universal rearrangements of the human genome.
Obtaining novel antibodies against specific protein targets is a widely important yet experimentally laborious process. Here, we introduce Germinal, a broadly enabling generative framework that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-throughput experimental testing.
Genome language models have emerged as a promising strategy for designing biological systems, but their ability to generate functional sequences at the scale of whole genomes has remained untested. Here, we report the first generative design of viable bacteriophage genomes.