Martín González Buitrón
@tinchogb.bsky.social
🇦🇷 PhD Student - CONICET
⚛️ Biotechnologist and Molecular Biologist - UNLP
💻 Bioinformatics - member of SBG - UNQ
🙌🏼 Programming student - UNQ
Argentina - Bs. As. - Bernal
https://gitlab.com/martingonzalezbuitron
⚛️ Biotechnologist and Molecular Biologist - UNLP
💻 Bioinformatics - member of SBG - UNQ
🙌🏼 Programming student - UNQ
Argentina - Bs. As. - Bernal
https://gitlab.com/martingonzalezbuitron
Reposted by Martín González Buitrón
Bluesky’s science takeover: 70% of Nature poll respondents use platform https://www.nature.com/articles/d41586-025-00177-1
January 24, 2025 at 4:36 PM
Bluesky’s science takeover: 70% of Nature poll respondents use platform https://www.nature.com/articles/d41586-025-00177-1
Reposted by Martín González Buitrón
Academics from poorer socio-economic backgrounds are more likely to
- not publish
- have outstanding publication records
- introduce more novel scientific concepts
- less likely to receive recognition, as measured by citations, Nobel Prize nominations, and awards.
www.nber.org/papers/w33289
- not publish
- have outstanding publication records
- introduce more novel scientific concepts
- less likely to receive recognition, as measured by citations, Nobel Prize nominations, and awards.
www.nber.org/papers/w33289
December 23, 2024 at 12:10 PM
Academics from poorer socio-economic backgrounds are more likely to
- not publish
- have outstanding publication records
- introduce more novel scientific concepts
- less likely to receive recognition, as measured by citations, Nobel Prize nominations, and awards.
www.nber.org/papers/w33289
- not publish
- have outstanding publication records
- introduce more novel scientific concepts
- less likely to receive recognition, as measured by citations, Nobel Prize nominations, and awards.
www.nber.org/papers/w33289
🧬 Just a funny thought about #CASP16 results
Won't somebody please think of the RNAs? 💭
Drop-in a paper to expose this issue, like:
- [When will RNA get its AlphaFold moment?](doi.org/10.1093/nar/...)
- [Thoughts on how to think (and talk) about RNA structure](doi.org/10.1073/pnas...)
Won't somebody please think of the RNAs? 💭
Drop-in a paper to expose this issue, like:
- [When will RNA get its AlphaFold moment?](doi.org/10.1093/nar/...)
- [Thoughts on how to think (and talk) about RNA structure](doi.org/10.1073/pnas...)
a group of cartoon characters are standing next to each other in a restaurant .
ALT: a group of cartoon characters are standing next to each other in a restaurant .
media.tenor.com
December 3, 2024 at 8:25 PM
🧬 Just a funny thought about #CASP16 results
Won't somebody please think of the RNAs? 💭
Drop-in a paper to expose this issue, like:
- [When will RNA get its AlphaFold moment?](doi.org/10.1093/nar/...)
- [Thoughts on how to think (and talk) about RNA structure](doi.org/10.1073/pnas...)
Won't somebody please think of the RNAs? 💭
Drop-in a paper to expose this issue, like:
- [When will RNA get its AlphaFold moment?](doi.org/10.1093/nar/...)
- [Thoughts on how to think (and talk) about RNA structure](doi.org/10.1073/pnas...)
Reposted by Martín González Buitrón
gonna start shamelessly crossposting some of my molecular movies from the Other Place. Starting with my favourite: showing how wacky reverse transcription can defeat viruses. Bonus: some noises 🎹🎻
November 18, 2024 at 7:05 PM
gonna start shamelessly crossposting some of my molecular movies from the Other Place. Starting with my favourite: showing how wacky reverse transcription can defeat viruses. Bonus: some noises 🎹🎻
Reposted by Martín González Buitrón
Data is the most fundamental requirement to build a good machine learning system.
Common challenges:
- Not having enough of it
- Poor-quality
- Nonrepresentative training data
- Not enough relevant features
- Too many irrelevant features
- Low diversity
Garbage in, garbage out.
Common challenges:
- Not having enough of it
- Poor-quality
- Nonrepresentative training data
- Not enough relevant features
- Too many irrelevant features
- Low diversity
Garbage in, garbage out.
November 30, 2024 at 2:00 PM
Data is the most fundamental requirement to build a good machine learning system.
Common challenges:
- Not having enough of it
- Poor-quality
- Nonrepresentative training data
- Not enough relevant features
- Too many irrelevant features
- Low diversity
Garbage in, garbage out.
Common challenges:
- Not having enough of it
- Poor-quality
- Nonrepresentative training data
- Not enough relevant features
- Too many irrelevant features
- Low diversity
Garbage in, garbage out.
Reposted by Martín González Buitrón
Reposted by Martín González Buitrón
The paper ”Stereochemistry in the disorder–order continuum of protein interactions” from my colleagues @estellaan.bsky.social, Johan Olsen, @bbkrage.bsky.social et al is now out:
doi.org/10.1038/s415... 🍝 🧪 🧬 🧶
doi.org/10.1038/s415... 🍝 🧪 🧬 🧶
November 27, 2024 at 5:21 PM
The paper ”Stereochemistry in the disorder–order continuum of protein interactions” from my colleagues @estellaan.bsky.social, Johan Olsen, @bbkrage.bsky.social et al is now out:
doi.org/10.1038/s415... 🍝 🧪 🧬 🧶
doi.org/10.1038/s415... 🍝 🧪 🧬 🧶
Reposted by Martín González Buitrón
Here is how Boltz-1 (green), DynamicBind (magenta), and GNINA (blue) dock a collection of random molecules. GNINA, using a classical sampling algorithm (MCMC) hits all concave regions while the ML samplers have distinct preferences. Boltz is the most likely to induce a fit.
November 22, 2024 at 6:27 PM
Here is how Boltz-1 (green), DynamicBind (magenta), and GNINA (blue) dock a collection of random molecules. GNINA, using a classical sampling algorithm (MCMC) hits all concave regions while the ML samplers have distinct preferences. Boltz is the most likely to induce a fit.
Reposted by Martín González Buitrón
Happy to announce that the latest UniProt NAR paper is now out. Find out what we've been up to here academic.oup.com/nar/advance-...
UniProt: the Universal Protein Knowledgebase in 2025
Abstract. The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely acce
academic.oup.com
November 18, 2024 at 9:47 AM
Happy to announce that the latest UniProt NAR paper is now out. Find out what we've been up to here academic.oup.com/nar/advance-...
Reposted by Martín González Buitrón
Hi TED! 👋
Out now in Science, we are finally ready to make our classification of all domains in AFDB v4 available to all!
A joint effort of @cathgene3d.bsky.social and the Jones group (PSIPRED), here's a link to the article
www.science.org/doi/10.1126/...
1/6 🧵⤵️
Out now in Science, we are finally ready to make our classification of all domains in AFDB v4 available to all!
A joint effort of @cathgene3d.bsky.social and the Jones group (PSIPRED), here's a link to the article
www.science.org/doi/10.1126/...
1/6 🧵⤵️
Exploring structural diversity across the protein universe with The Encyclopedia of Domains
The AlphaFold Protein Structure Database (AFDB) contains more than 214 million predicted protein structures composed of domains, which are independently folding units found in multiple structural and ...
www.science.org
November 16, 2024 at 2:59 PM
Hi TED! 👋
Out now in Science, we are finally ready to make our classification of all domains in AFDB v4 available to all!
A joint effort of @cathgene3d.bsky.social and the Jones group (PSIPRED), here's a link to the article
www.science.org/doi/10.1126/...
1/6 🧵⤵️
Out now in Science, we are finally ready to make our classification of all domains in AFDB v4 available to all!
A joint effort of @cathgene3d.bsky.social and the Jones group (PSIPRED), here's a link to the article
www.science.org/doi/10.1126/...
1/6 🧵⤵️
Reposted by Martín González Buitrón
🚀 P2Rank 2.5 now offers #ChimeraX visualizations of ligand-binding site predictions (alongside #PyMOL ones)! Huge thanks to @javierutges.bsky.social and ChimeraX team for inspiration and help.
Release Details: github.com/rdk/p2rank/r...
💡 Feedback welcome!
#Bioinformatics #DrugDiscovery
Release Details: github.com/rdk/p2rank/r...
💡 Feedback welcome!
#Bioinformatics #DrugDiscovery
November 16, 2024 at 7:15 PM
🚀 P2Rank 2.5 now offers #ChimeraX visualizations of ligand-binding site predictions (alongside #PyMOL ones)! Huge thanks to @javierutges.bsky.social and ChimeraX team for inspiration and help.
Release Details: github.com/rdk/p2rank/r...
💡 Feedback welcome!
#Bioinformatics #DrugDiscovery
Release Details: github.com/rdk/p2rank/r...
💡 Feedback welcome!
#Bioinformatics #DrugDiscovery
Reposted by Martín González Buitrón
This is the first fully open source release of a AF3 like model. Awesome! Congratulations to the team.
Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with Jeremy, Saro, and an amazing team at MIT and Genesis Therapeutics. A thread!
November 17, 2024 at 5:13 PM
This is the first fully open source release of a AF3 like model. Awesome! Congratulations to the team.