2 citations · 2 across the 4 of their papers we have counts for
4 papers
AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents
Edward De Brouwer, Carl Edwards, Alexander Wu +9
Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational model of cellular behavior tha…
HypoGeneAgent: A Hypothesis Language Agent for Gene-Set Cluster Resolution Selection Using Perturb-seq Datasets
Ying Yuan, Xing-Yue Monica Ge, Aaron Archer Waterman +8
Large-scale single-cell and Perturb-seq investigations routinely involve clustering cells and subsequently annotating each cluster with Gene-Ontology (GO) terms to elucidate the un…
Contextualizing biological perturbation experiments through language
Menghua Wu, Russell Littman, Jacob Levine +4
High-content perturbation experiments allow scientists to probe biomolecular systems at unprecedented resolution, but experimental and analysis costs pose significant barriers to w…
Learning Identifiable Factorized Causal Representations of Cellular Responses
Haiyi Mao, Romain Lopez, Kai Liu +4
The study of cells and their responses to genetic or chemical perturbations promises to accelerate the discovery of therapeutic targets. However, designing adequate and insightful…