Gonzalo Parra
@gonzaparra.bsky.social
740 followers 260 following 120 posts
Ramón y Cajal Junior Group Leader @BSC_CNS 🇦🇷🇪🇸🏳️‍🌈 ENFJ | Bioinformatics | 3DSIG Co-Chair | @fi_uner, @exactas_uba, @mpi_bpc, @embl, @dkfz alumnus | @iscb BoD | Opinions my own
Posts Media Videos Starter Packs
Reposted by Gonzalo Parra
gonzaparra.bsky.social
🚀 As first official act, we are hiring! 🎓
We’re looking for a PhD student to work at the interface of computational biophysics, machine learning & human mutations. 📌 FPI fellowship, 4 years fully funded!

More information here:
www.bsc.es/join-us/job-...
gonzaparra.bsky.social
After months of buildup, it’s finally real! 🎉 The Evolutionary Systems Biophysics Group (ESBG) is officially alive at @bsc-cns.bsky.social . Proud to start this new adventure as a Ramon y Cajal Junior Group Leader🧬
Thanks to all who have been part of this process!
tinyurl.com/4r9vf4zx
Reposted by Gonzalo Parra
gonzaparra.bsky.social
After months of buildup, it’s finally real! 🎉 The Evolutionary Systems Biophysics Group (ESBG) is officially alive at @bsc-cns.bsky.social . Proud to start this new adventure as a Ramon y Cajal Junior Group Leader🧬
Thanks to all who have been part of this process!
tinyurl.com/4r9vf4zx
gonzaparra.bsky.social
🚀 As first official act, we are hiring! 🎓
We’re looking for a PhD student to work at the interface of computational biophysics, machine learning & human mutations. 📌 FPI fellowship, 4 years fully funded!

More information here:
www.bsc.es/join-us/job-...
gonzaparra.bsky.social
After months of buildup, it’s finally real! 🎉 The Evolutionary Systems Biophysics Group (ESBG) is officially alive at @bsc-cns.bsky.social . Proud to start this new adventure as a Ramon y Cajal Junior Group Leader🧬
Thanks to all who have been part of this process!
tinyurl.com/4r9vf4zx
gonzaparra.bsky.social
After months of buildup, it’s finally real! 🎉 The Evolutionary Systems Biophysics Group (ESBG) is officially alive at @bsc-cns.bsky.social . Proud to start this new adventure as a Ramon y Cajal Junior Group Leader🧬
Thanks to all who have been part of this process!
tinyurl.com/4r9vf4zx
Reposted by Gonzalo Parra
proflhunter.bsky.social
Whole brain dynamics in the ~10s regime shows synchronized propagation of topographically organized rotating waves, driving behavior, calcium fluxes, band-limited power, metabolism, blood flow, etc. All can be predicted from time-lagged embedding of pupil size alone! www.nature.com/articles/s41...
Arousal as a universal embedding for spatiotemporal brain dynamics - Nature
Reframing of arousal as a latent dynamical system can reconstruct multidimensional measurements of large-scale spatiotemporal brain dynamics on the timescale of seconds in mice.
www.nature.com
Reposted by Gonzalo Parra
zaminiqbal.bsky.social
Delighted to see our paper studying the evolution of plasmids over the last 100 years, now out! Years of work by Adrian Cazares, also Nick Thomson @sangerinstitute.bsky.social - this version much improved over the preprint. Final version should be open access, apols.
Thread 1/n
gonzaparra.bsky.social
LinkedIn just notified about my 4th year annyversary working at the @bsc-cns.bsky.social, time flies!!! It's been a great chapter so far in my scientific journey!! A lot of projects on the list! #ILoveScience
Reposted by Gonzalo Parra
saezlab.bsky.social
🥁 Check out our new preprint on OmniPath, the prior knowledge resource for #SystemsBiology, and its brand-new OmniPath Explorer web app! 🥳

📖 Preprint: www.biorxiv.org/content/10.1...
🔍 Explorer: explore.omnipathdb.org

OmniPath integrates 160+ resources for multi-omics analysis & modeling.

🧶⬇️
Reposted by Gonzalo Parra
lindorfflarsen.bsky.social
New review on computational design of intrinsically disordered proteins 🖥️🍝 by @giuliotesei.bsky.social @fpesce.bsky.social & 👴

doi.org/10.48550/arX...
Figure 3 from the paper with the caption: "Role of machine learning in de novo design of IDRs. (A) Machine-learning models can be trained on diverse data sources, from molecular dynamics simulations to annotations of cellular localization and protein structures from the Protein Data Bank. (B) Often implemented as neural networks using sequence-encoded features as input, these models can initially be trained on a limited region of sequence space as surrogate models. Through active learning, additional simulations are performed during the design campaign to generate new data, and the surrogate model is retrained on the expanded dataset to progressively improve its accuracy. (C) Machine-learning models have been developed to predict biophysical observables, biological annotations, and protein structures. When combined, machine-learning models can be used to identify a set of sequences that strike a trade-off between multiple design objectives, defining a Pareto front."
Reposted by Gonzalo Parra
stephanieaw.bsky.social
Structural bioinformatics is incredibly powerful on its own or when paired with theory or experiment. One of the PDB's superpowers isn’t from one structure, but comparing many to uncover folds, binding sites, and subtle conformational shifts. chemrxiv.org/engage/chemr...
10 Rules for a Structural Bioinformatic Analysis
The Protein Data Bank (PDB) is one of the richest open‑source repositories in biology, housing over 277,000 macromolecular structural models alongside much of the experimental data that underpins thes...
chemrxiv.org
Reposted by Gonzalo Parra
judewells.bsky.social
It was lovely to speak at the CATH 30 symposium, celebrating 30 years of the @cathgene3d.bsky.social protein structure classification database. I was presenting recent work on our new generative protein-family language model: preprint coming soon.
gonzaparra.bsky.social
That is great!!! It is for sure super useful! Thanks a lot!
gonzaparra.bsky.social
Dear Colleagues. We are in need of a molecular dynamics trajectory of a "folding upon binding event" where a protein with an IDR folds into its partner. Do you know of any published and available trajectory that we could use?? Thanksss a lot!
Reposted by Gonzalo Parra
cathgene3d.bsky.social
Rob Finn on MGnify, everything bacteria and functions in different environments
Reposted by Gonzalo Parra
cathgene3d.bsky.social
Now Maria Martín from UniProt is telling us how AI-based tools are shaping the future of one of the key resources for protein sequences and function.
Reposted by Gonzalo Parra
cathgene3d.bsky.social
From structures to sequences, now Alex Bateman and the quest to annotate and classify all proteins!
Reposted by Gonzalo Parra
cathgene3d.bsky.social
Starting our afternoon session with a talk by Sameer Velankar, of PDBe and AFDB fame among other endeavours!
Reposted by Gonzalo Parra
cathgene3d.bsky.social
And now @gonzaparra.bsky.social on his first talk on protein frustration as a PI! Well done!
Reposted by Gonzalo Parra
cathgene3d.bsky.social
David Jones, on novel folds in AFDB and CATH’s founding being celebrated at a now-closed Pizza place in Euston Station