Daniela Kalafatovic
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dani-deshpet.bsky.social
Daniela Kalafatovic
@dani-deshpet.bsky.social
Reposted by Daniela Kalafatovic
🌟Look fwd to welcoming @dani-deshpet.bsky.social as lecturer in our #BiomolecularInteractions #Modelling Course. 🖥️ Join us to learn about uncovering peptide self‑assembly using adaptive, generative machine learning models!🔗bit.ly/3ZUSXNX 🗓️14Oct'25
@molbiom.bsky.social
@i3suporto.bsky.social #Porto
July 18, 2025 at 11:20 AM
Reposted by Daniela Kalafatovic
Very pleased to have @dani-deshpet.bsky.social as a lecturer in @mobilise.bsky.social training course! She is Chair of @snoopy-costaction.bsky.social and will share insights on #machine #learning for #peptide design. Don´t miss the chance to learn about #molecular & #professional #interactions! 😊
🌟Look fwd to welcoming @dani-deshpet.bsky.social as lecturer in our #BiomolecularInteractions #Modelling Course. 🖥️ Join us to learn about uncovering peptide self‑assembly using adaptive, generative machine learning models!🔗bit.ly/3ZUSXNX 🗓️14Oct'25
@molbiom.bsky.social
@i3suporto.bsky.social #Porto
July 18, 2025 at 6:10 PM
Check out our new review on Using Machine Learning to Fast-Track Peptide Nanomaterial Discovery | ACS Nano pubs.acs.org/doi/full/10....
Using Machine Learning to Fast-Track Peptide Nanomaterial Discovery
Peptides can serve as building blocks for supramolecular materials because of their unique ability to self-assemble, offering potential applications in drug delivery, tissue engineering, and nanotechn...
pubs.acs.org
May 30, 2025 at 8:17 AM
Reposted by Daniela Kalafatovic
Materials Advances is pleased to announce an open call for papers for our upcoming collection on Supramolecular Peptide & Protein Systems, guest edited by @dani-deshpet.bsky.social, Ana Garcia, Veronica Dodero, Ivan Sasselli and Jacek Wychowaniec.
Learn more here: blogs.rsc.org/jm/2025/05/0...
May 21, 2025 at 11:01 AM
Check out our latest paper on the application of ML and generative models on peptide self-assembly prediction
www.nature.com/articles/s42...
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning - Nature Machine Intelligence
A generative model guided by a machine-learning-based classifier capable of assessing unexplored regions of the peptide space in the search for new self-assembling sequences.
www.nature.com
February 1, 2025 at 4:57 PM