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Automating the Practice of Science -- Opportunities, Challenges, and Implications

Autor: Musslick, Sebastian, Bartlett, Laura K., Chandramouli, Suyog H., Dubova, Marina, Gobet, Fernand, Griffiths, Thomas L., Hullman, Jessica, King, Ross D., Kutz, J. Nathan, Lucas, Christopher G., Mahesh, Suhas, Pestilli, Franco, Sloman, Sabina J., Holmes, William R.

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery,

Externí odkaz: http://arxiv.org/abs/2409.05890

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Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture

Autor: Abdel-Rehim, Abbi, Orhobor, Oghenejokpeme, Griffiths, Gareth, Soldatova, Larisa, King, Ross D.

The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for patients with tumours presenting well-defined mutations. However, the field is still in its infancy, an

Externí odkaz: http://arxiv.org/abs/2408.13012

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Genesis: Towards the Automation of Systems Biology Research

Autor: Tiukova, Ievgeniia A., Brunnsåker, Daniel, Bjurström, Erik Y., Gower, Alexander H., Kronström, Filip, Reder, Gabriel K., Reiserer, Ronald S., Korovin, Konstantin, Soldatova, Larisa B., Wikswo, John P., King, Ross D.

The cutting edge of applying AI to science is the closed-loop automation of scientific research: robot scientists. We have previously developed two robot scientists: `Adam' (for yeast functional biology), and `Eve' (for early-stage drug design)). We

Externí odkaz: http://arxiv.org/abs/2408.10689

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The Use of AI-Robotic Systems for Scientific Discovery

Autor: Gower, Alexander H., Korovin, Konstantin, Brunnsåker, Daniel, Kronström, Filip, Reder, Gabriel K., Tiukova, Ievgeniia A., Reiserer, Ronald S., Wikswo, John P., King, Ross D.

The process of developing theories and models and testing them with experiments is fundamental to the scientific method. Automating the entire scientific method then requires not only automation of the induction of theories from data, but also experi

Externí odkaz: http://arxiv.org/abs/2406.17835

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Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment

Autor: Abdel-Rehim, Abbi, Zenil, Hector, Orhobor, Oghenejokpeme, Fisher, Marie, Collins, Ross J., Bourne, Elizabeth, Fearnley, Gareth W., Tate, Emma, Smith, Holly X., Soldatova, Larisa N., King, Ross D.

Large language models (LLMs) have transformed AI and achieved breakthrough performance on a wide range of tasks that require human intelligence. In science, perhaps the most interesting application of LLMs is for hypothesis formation. A feature of LL

Externí odkaz: http://arxiv.org/abs/2405.12258

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