How AI, robotics, and modular design are transforming single-cell and spatial biology into scalable, precision-driven engines of discovery.
A streamlined, automated process helps scientists coordinate site-ready production-level whole genome sequencing results.
Although machine learning (ML) and other artificial intelligence tools are useful to analyze the massive amounts of data being generated by sequencing technologies, most ML tools are difficult for non ...
SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...
PacBio and Google Collaborate to Use Machine Learning to Optimize Long-Read Sequencing Data Analysis
Initial proof-of-concept work suggests strong potential to further improve PacBio’s highly accurate HiFi Sequencing with Google deep learning technologies MENLO PARK, Calif., Jan. 11, 2022 (GLOBE ...
BOSTON, Oct. 30, 2024 /PRNewswire/ -- Volta Labs™, a genomics applications company, announced today that it has joined the PacBio Compatible program, further expanding the partnership between Volta ...
Join this webinar to learn how the Bioscience Core Lab at KAUST has automated their PacBio Kinnex library prep workflow on Opentrons robots to facilitate high-throughput RNA sequencing. Angel Angelov ...
Tensor is the first instrument that fully automates the complete single cell sequencing workflow for up to 32 samples, from cell suspension to sequencing-ready library. This alliance combines ...
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