The human kidney contains highly specialized cell populations. Despite numerous single-cell and single-nucleus transcriptomics studies, differences in cohorts, technologies, analytical pipelines, and annotation frameworks have limited the ability to define consensus kidney cell states, identify disease-associated popul...
Konstantinos Stasinos, Han-Chen Wang, A. Predeus et al.· bioRxiv· 0 citations
Target discovery in functional genomics remains largely manual and time-consuming, lacking systematic tools for efficient and reproducible gene-level hypothesis generation. We introduce AutoScreen, an AI co-scientist system supporting target discovery through both Pre-screen Design, which constructs perturbation librar...
Yuan-Hao Qu, Xu-Feng Liu, Xiao-Tong Wang et al.· bioRxiv· 0 citations
Perturb-ME, along with agentic interpretation, provide a scalable framework for comprehensive functional discovery from phenotype-enriched genetic screens and combines genome-scale CRISPR screening, phenotype-based enrichment and multimodal single-cell profiling.
Han-Chen Wang, Jiacheng Gu, Chris J. Frangieh et al.· bioRxiv· 0 citations
Biomni envisions artificial intelligence augmenting human scientists and accelerating discovery by interpreting multi-modal datasets, optimizing protein stability, orchestrating wet-lab instruments, and generating experimentally testable protocols.
Kexin Huang, Serena Zhang, Hanchen Wang et al.· Science· 19 citations· ⚡2
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