Deep Learning for 3D Protein Structure Predictions – Giulia Crocioni on DeepRank2

#8: Giulia Crocioni joins Arfon and Abby to discuss DeepRank2, a deep learning framework for 3D protein structure predictions. Giulia is a Research Software Engineer at the Netherlands eScience Center where she uses different machine learning techniques to develop and contribute to methodologies and applications to answer life sciences research questions. You can follow Giulia on LinkedIn See the show notes: https://blog.joss.theoj.org/2024/04/josscast-8-deep-learning-for-3d-protein-structure-predictions

Episode highlights: - [00:02:16] Giulia introduces herself and her work at the Netherlands eScience Centre in the Life Sciences section. - [00:04:09] Introducing DeepRank2: An open-source deep learning framework for data mining of protein-protein interfaces or single-residue variants. - [00:10:14] Target audiences (researchers, developers) and applications (drug design, cancer vaccine development) - [00:13:48] Ecosystem overview from complementary projects like AlphaFold, to training data sources, to using PyTorch. - [00:23:27] Open Source & Contributions Links:

• JOSS paper: https://joss.theoj.org/papers/10.21105/joss.05983
• DeepRank2 repository: https://github.com/DeepRank/deeprank2
• Netherlands eScience Center: https://www.esciencecenter.nl/
• Giulia on LinkedIn: https://www.linkedin.com/in/giulia-crocioni/
• The Journal of Open Source Software (Twitter/X, blog)
• @arfon on (fosstodon, Linkedin, GitHub, website)
• @abbycabs on (Twitter/X, hachyderm, bsky, Linkedin, GitHub, website)
• Donate to JOSS

See the show notes: https://blog.joss.theoj.org/2024/04/josscast-8-deep-learning-for-3d-protein-structure-predictions

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