arXiv:2604.02511v1 Announce Type: new
Abstract: Public pooled single-cell perturbation atlases are valuable resources for studying transcription factor (TF) function, but downstream re-analysis can be limited by incomplete deposited metadata and missi…
arXiv:2604.01949v2 Announce Type: replace
Abstract: The scale of biological datasets now routinely exceeds system memory, making data access rather than model computation the primary bottleneck in training machine-learning models. This bottleneck is p…
arXiv:2604.02886v1 Announce Type: cross
Abstract: We study high-dimensional mediation analysis in which exposures, mediators, and outcomes are all multivariate, and both exposures and mediators may be high-dimensional. We formalize this as a many (exp…
arXiv:2604.01949v1 Announce Type: new
Abstract: The scale of biological datasets now routinely exceeds system memory, making data access rather than model computation the primary bottleneck in training machine-learning models. This bottleneck is parti…
arXiv:2604.00058v1 Announce Type: cross
Abstract: Genotype imputation enables dense variant coverage for genome-wide association and risk-prediction studies, yet conventional reference-panel methods remain limited by ancestry bias and reduced rare-var…
arXiv:2604.00065v1 Announce Type: cross
Abstract: Multi-omic datasets offer opportunities for improved biomarker discovery in cancer research, but their high dimensionality and limited sample sizes make identifying compact and effective biomarker pane…
arXiv:2509.20702v2 Announce Type: replace-cross
Abstract: Recent advances in large language model (LLM) embeddings have enabled powerful representations for biological data, but most applications to date focus on gene-level information. We present one…
arXiv:2603.26858v1 Announce Type: new
Abstract: Single-cell RNA-seq data analysis typically requires representations that capture heterogeneous local structure across multiple scales while remaining stable and interpretable. In this work, we propose a…
arXiv:2603.27145v1 Announce Type: cross
Abstract: As immunotherapies become standard cancer treatments, it is increasingly important to identify a patient’s immune profile, which encompasses the activity of immune cells within the tumor microenvironme…
arXiv:2603.25240v1 Announce Type: cross
Abstract: Modeling cellular states and predicting their responses to perturbations are central challenges in computational biology and the development of virtual cells. Existing foundation models for single-cell…