Daniela Kalafatovic
@dani-deshpet.bsky.social
📤 22
📥 37
📝 2
https://deshpetlab.uniri.hr/
reposted by
Daniela Kalafatovic
MOBILIsE_ERA-CHAIR
5 months ago
🌟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
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reposted by
Daniela Kalafatovic
Molecular Biomaterials Group at i3S, led by Helena Azevedo
5 months ago
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
! 😊
add a skeleton here at some point
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Check out our new review on Using Machine Learning to Fast-Track Peptide Nanomaterial Discovery | ACS Nano
pubs.acs.org/doi/full/10....
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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...
https://pubs.acs.org/doi/full/10.1021/acsnano.5c00670
7 months ago
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reposted by
Daniela Kalafatovic
Materials Advances
7 months ago
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...
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Check out our latest paper on the application of ML and generative models on peptide self-assembly prediction
www.nature.com/articles/s42...
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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.
https://www.nature.com/articles/s42256-024-00928-1
11 months ago
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