Epigenetic regulation involves the coordinated interplay of diverse proteins. We present COMBINE, a high-throughput platform that tests over 50,000 pairs of epigenetic effector domains up to 2,094 amino acids in length for their ability to modulate endogenous human gene transcription.
Here, we develop a multi-scale screening framework that integrates bulk patient transcriptomics, functional in vivo genetic screening, and single-cell transcriptomic and epigenomic profiling to nominate chromatin organizers that modulate ITH in breast cancer.
To identify strategies to enhance the utility of third-generation bi-steric mTORC1 inhibitors, we performed genome-scale CRISPR interference chemogenomics screens, which revealed that mTORC1 inhibitor-mediated cytostasis leaves cells exquisitely dependent on the lipid peroxide scavenging enzyme GPX4.
We introduce BioReason-Pro, the first multimodal reasoning large language model (LLM) for protein function prediction that integrates protein embeddings with biological context to generate structured reasoning traces.
Heterogeneity in cancer gene expression is typically linked to genetic and epigenetic alteration. Here, we systematically measured messenger RNA (mRNA) dynamics across diverse breast cancer models, revealing that mRNA stability substantially shapes gene expression variability.
Here, by charting a high-resolution map of microbiome ageing and its functional consequences throughout the lifespan of mice, we identify a mechanism by which inhibition of gut–brain signalling during ageing results in impaired neuronal activation in the hippocampus and loss of memory encoding.
The influence of lifestyle factors on the effectiveness of T cell-mediated cancer immunotherapies remains unclear. Here, we demonstrate that the ketogenic diet-induced ketone metabolite β-hydroxybutyrate (BHB) augments chimeric antigen receptor T cell function across multiple preclinical cancer models.
AI models that learn information from genomic sequences have advanced prediction and design capabilities. Here we introduce Evo 2, a biological foundation model trained on 9 trillion DNA base pairs from a highly curated genomic atlas spanning all domains of life to have a 1 million token context window with single-nucleotide resolution.
Vitamins are essential metabolites that must be obtained from external sources. In modern times, they have become widely available, leading to their ad hoc consumption. We developed a nutritional genomics framework to systematically identify monogenic diseases responsive to micronutrient modulation.
The clinical success of cancer drug candidates depends on efficacy across many different individuals, but we currently rely on a limited set of in vivo preclinical models. Here, to address this limitation, we introduce GENEVA, a scalable single-cell-resolution platform for measuring responses to drug perturbations.