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Arboreto is a specialized computational tool designed for inferring gene regulatory networks (GRNs) from large-scale gene expression data. It enables researchers and bioinformaticians to map transcription factor-target gene interactions by leveraging high-performance machine learning algorithms such as gradient boosting and random forests. Optimized for modern genomics, it scales seamlessly from local machines to multi-node clusters via Dask, making it an essential skill for analyzing complex bulk and single-cell RNA-seq datasets directly within the Claude development environment.
