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Showing 1–11 of 11 results
Advanced filters: Author: Noelia Ferruz Clear advanced filters

  • For our fifth anniversary, we reconnected with authors of recent Comments and Perspectives in Nature Machine Intelligence and asked them how the topic they wrote about developed. We also wanted to know what other topics in AI they found exciting, surprising or worrying, and what their hopes and expectations are for AI in 2024—and the next five years. A recurring theme is the ongoing developments in large language models and generative AI, their transformative effect on the scientific process and concerns about ethical implications.

    • Noelia Ferruz
    • Marinka Zitnik
    • Francesco Stella
    Special Features
    Nature Machine Intelligence
    Volume: 6, P: 6-12

  • Both proteins and natural language are essentially based on a sequential code, but feature complex interactions at multiple scales, which can be useful when transferring machine learning models from one domain to another. In this Review, Ferruz and Höcker summarize recent advances in language models, such as transformers, and their application to protein design.

    • Noelia Ferruz
    • Birte Höcker
    Reviews
    Nature Machine Intelligence
    Volume: 4, P: 521-532

  • Collagen triple helices are found in all the three domains of life as well as viruses. Here, the authors show that collagens have converged on a similar folding mechanism that employs salt bridge interactions to guide the triple helix assembly.

    • Jean-Daniel Malcor
    • Noelia Ferruz
    • Abhishek A. Jalan
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-19

  • Protein design aims to build novel proteins customized for specific purposes, thereby holding the potential to tackle many environmental and biomedical problems. Here the authors apply some of the latest advances in natural language processing, generative Transformers, to train ProtGPT2, a language model that explores unseen regions of the protein space while designing proteins with nature-like properties.

    • Noelia Ferruz
    • Steffen Schmidt
    • Birte Höcker
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-10

  • A deep learning algorithm for protein structure prediction is used in reverse for de novo protein design.

    • Noelia Ferruz
    • Birte Höcker
    News & Views
    Nature Biotechnology
    Volume: 40, P: 171-172