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Showing 1–7 of 7 results
Advanced filters: Author: Gabe Gomes Clear advanced filters

  • A two-phase machine-learning-based tool making use of high-throughput experimentation is introduced to examine the connections between chemical and protein sequence space and predict productive biocatalytic reactions among substrate and enzyme pairs.

    • Alexandra E. Paton
    • Daniil A. Boiko
    • Alison R. H. Narayan
    ResearchOpen Access
    Nature
    Volume: 646, P: 108-116

  • Coscientist is an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation.

    • Daniil A. Boiko
    • Robert MacKnight
    • Gabe Gomes
    ResearchOpen Access
    Nature
    Volume: 624, P: 570-578

  • This Perspective highlights the potential integrations of large language models (LLMs) in chemical research and provides guidance on the effective use of LLMs as research partners, noting the ethical and performance-based challenges that must be addressed moving forward.

    • Robert MacKnight
    • Daniil A. Boiko
    • Gabe Gomes
    Reviews
    Nature Computational Science
    Volume: 5, P: 715-726

  • In an inter-laboratory study, the authors compare the accuracy and performance of three optical density calibration protocols (colloidal silica, serial dilution of silica microspheres, and colony-forming unit (CFU) assay). They demonstrate that serial dilution of silica microspheres is the best of these tested protocols, allowing precise and robust calibration that is easily assessed for quality control and can also evaluate the effective linear range of an instrument.

    • Jacob Beal
    • Natalie G. Farny
    • Jiajie Zhou
    ResearchOpen Access
    Communications Biology
    Volume: 3, P: 1-29