GAMA Miguel Angel
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miangoar.bsky.social
GAMA Miguel Angel
@miangoar.bsky.social
220 followers 190 following 96 posts
Biologist that navigate in the oceans of diversity through space-time

Protein evolution, metagenomics, AI/ML/DL

Website https://miangoaren.github.io/
Posts Replies Media Videos
Reposted by GAMA Miguel Angel
hansonmark.bsky.social
We wrote the Strain on scientific publishing to highlight the problems of time & trust. With a fantastic group of co-authors, we present The Drain of Scientific Publishing:

a 🧵 1/n

Drain: arxiv.org/abs/2511.04820
Strain: direct.mit.edu/qss/article/...
Oligopoly: direct.mit.edu/qss/article/...
A table showing profit margins of major publishers. A snippet of text related to this table is below. 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year. A figure detailing the drain on researcher time. 1. The four-fold drain 1.2 Time The number of papers published each year is growing faster than the scientific workforce, with the number of papers per researcher almost doubling between 1996 and 2022 (Figure 1A). This reflects the fact that publishers’ commercial desire to publish (sell) more material has aligned well with the competitive prestige culture in which publications help secure jobs, grants, promotions, and awards. To the extent that this growth is driven by a pressure for profit, rather than scholarly imperatives, it distorts the way researchers spend their time. The publishing system depends on unpaid reviewer labour, estimated to be over 130 million unpaid hours annually in 2020 alone (9). Researchers have complained about the demands of peer-review for decades, but the scale of the problem is now worse, with editors reporting widespread difficulties recruiting reviewers. The growth in publications involves not only the authors’ time, but that of academic editors and reviewers who are dealing with so many review demands. Even more seriously, the imperative to produce ever more articles reshapes the nature of scientific inquiry. Evidence across multiple fields shows that more papers result in ‘ossification’, not new ideas (10). It may seem paradoxical that more papers can slow progress until one considers how it affects researchers’ time. While rewards remain tied to volume, prestige, and impact of publications, researchers will be nudged away from riskier, local, interdisciplinary, and long-term work. The result is a treadmill of constant activity with limited progress whereas core scholarly practices – such as reading, reflecting and engaging with others’ contributions – is de-prioritized. What looks like productivity often masks intellectual exhaustion built on a demoralizing, narrowing scientific vision. A table of profit margins across industries. The section of text related to this table is below: 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year. The costs of inaction are plain: wasted public funds, lost researcher time, compromised scientific integrity and eroded public trust. Today, the system rewards commercial publishers first, and science second. Without bold action from the funders we risk continuing to pour resources into a system that prioritizes profit over the advancement of scientific knowledge.
November 11, 2025 at 11:52 AM
miangoar.bsky.social
I strongly recommend making cat-based diagrams to illustrate complex topics in protein science: "Figure 4 considers [...] invariance and equivariance with respect to translations and rotations in 3D. For illustration purposes, the figure includes a series of cat cartoons in 2D."
October 24, 2025 at 5:47 AM
miangoar.bsky.social
I just want to create hype and say that I made a 10-class course to introduce people to AI-driven protein design. It’s around 750 slides and will be freely available for anyone who wants to use them and, most importantly, improve them. Stay tuned :)
October 9, 2025 at 5:59 PM
Reposted by GAMA Miguel Angel
claudiaalcar.bsky.social
Happy to share Piecing Together the History of Protein Folds From a Fragmented Evolutionary Record 🧪
It appears as part of a Special Section in @genomebiolevol.bsky.social organized by @cpuentelelievre.bsky.social @proteinmechanic.bsky.social and J. Douglas

doi.org/10.1093/gbe/...
Piecing Together the History of Protein Folds From a Fragmented Evolutionary Record
Abstract. Protein folds are structural units defined by the number, type, arrangement, and orientation of their core secondary structural elements. The uni
doi.org
September 15, 2025 at 7:52 AM
Reposted by GAMA Miguel Angel
evodivmet.bsky.social
🫡
September 12, 2025 at 1:10 AM
Reposted by GAMA Miguel Angel
sberry.bsky.social
This is a very cool ancestral reconstruction study by @krishnareddy.bsky.social et al. that I recommend reading! @rachellegaudet.bsky.social and I thought it was so interesting that we wrote a News & Views about it, check it out: rdcu.be/eCfyl
August 26, 2025 at 4:28 AM
Reposted by GAMA Miguel Angel
kevinkaichuang.bsky.social
If you're an undergrad and want to intern with me, this is where you need to apply!
msftresearch.bsky.social Microsoft Research @msftresearch.bsky.social · Sep 12
The Microsoft Research Undergraduate Internship Program offers 12-week internships in our Redmond, NYC, or New England labs for rising juniors and seniors who are passionate about technology. Apply by October 6: msft.it/6015scgSJ
September 13, 2025 at 10:42 AM
Reposted by GAMA Miguel Angel
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
September 11, 2025 at 2:28 PM
miangoar.bsky.social
This is a breakthrough for protein science🔥AFAIK this is the largest protein DB, with >100B seqs (3B clustered at 50%). New biology will come from LOGAN: new folds, topologies, etc. You can also improve your AlphaFold models by building better MSAs. Future AI models will also use LOGAN for training
September 5, 2025 at 4:51 PM
Reposted by GAMA Miguel Angel
rayanchikhi.bsky.social
🌎👩‍🔬 For 15+ years biology has accumulated petabytes (million gigabytes) of🧬DNA sequencing data🧬 from the far reaches of our planet.🦠🍄🌵

Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.

doi.org/10.1101/2024...
September 3, 2025 at 8:39 AM
miangoar.bsky.social
1/13 🧵 Today, Bindcraft was published in
@nature.com , one of the most famous AIs in biology for designing protein–protein interactions (PPI). In my opinion. Bindcraft represents one of the most important advances in the post–AlphaFold2 era.
August 27, 2025 at 7:54 PM
miangoar.bsky.social
Does anyone know of a recent comparison of the main structural classification schemes of proteins and guidance on when to choose one? Something like this but including ECOD and perhaps seq-based schemes like Pfam, SUPERFAMILY and CDD.

Img source (2020)
pubmed.ncbi.nlm.nih.gov/32302382/
August 27, 2025 at 2:16 AM
Reposted by GAMA Miguel Angel
genomebiolevol.bsky.social
In a new GBE Review, @cpuentelelievre.bsky.social @proteinmechanic.bsky.social & J. Douglas give an overview on protein structural phylogenetics, how to obtain evolutionary insights from structural data, and key applications and future directions.

🔗 doi.org/10.1093/gbe/evaf139

#genome #evolution
Puente-Lelievre et al. have systematically reviewed how protein structures can be used to trace evolutionary histories. This rapidly advancing field has not yet caught up with the burgeoning databases of high quality protein structure predictions provided by AlphaFold and other tools.
August 26, 2025 at 4:29 PM
miangoar.bsky.social
Hi @milot.bsky.social @martinsteinegger.bsky.social :) It appears that there is a problem with the FoldManson webserver. It does not allow load structures using accessions from PDB/UniProt/BFVD. e.g., when I tried with pdbID 1zg4, the error said "1 not found." The same occurs with any other acc.
August 26, 2025 at 6:15 PM
Reposted by GAMA Miguel Angel
martinsteinegger.bsky.social
Folddisco webserver result view update:
- Added description texts for AFDB
- Integrated TaxoView taxonomy visualization & filter by @sunjaelee.bsky.social
- Inter-residue distance clustering by DBSCAN to explore motif diversity.
🌐 search.foldseek.com/folddisco
📄 www.biorxiv.org/content/10.1...
July 22, 2025 at 6:11 PM
Reposted by GAMA Miguel Angel
audeber.bsky.social
🦠🧍‍♀️From bacterial to human immunity.

We report in @science.org the discovery of a human homolog of SIR2 antiphage proteins that participates in the TLR pathway of animal innate immunity.
Co-led wt @enzopoirier.bsky.social by D. Bonhomme and @hugovaysset.bsky.social

www.science.org/doi/10.1126/...
www.science.org
July 24, 2025 at 6:23 PM
Reposted by GAMA Miguel Angel
debnathghosal.bsky.social
📣 New paper alert!
One of the most exciting projects we've done in recent years is now out on BioRxiv: "An Asgard archaeon from a modern analog of ancient microbial mats".

Glimpse into early complex life! ❄️🦠 🔬🧬

www.biorxiv.org/content/10.1.... A thread...
An Asgard archaeon from a modern analog of ancient microbial mats
It has been proposed that eukaryotic cells evolved via symbiosis between sulfate-reducing bacteria and hydrogen-producing archaea. Here we describe a highly enriched culture of a novel Asgard archaeon...
www.biorxiv.org
July 25, 2025 at 1:29 PM
Reposted by GAMA Miguel Angel
noahfierer.bsky.social
New pre-print from my group - project led by PhD student Michael Hoffert. We set out on a daunting mission to generate a 'periodic table' of bacterial diversity (1/6) www.biorxiv.org/content/10.1...
A periodic table of bacteria?: Mapping bacterial diversity in trait space
Bacterial diversity can be overwhelming. There is an ever-expanding number of bacterial taxa being discovered, but many of these taxa remain uncharacterized with unknown traits and environmental prefe...
www.biorxiv.org
July 18, 2025 at 4:44 PM
Reposted by GAMA Miguel Angel
clauswilke.com
AlphaFold is great, but contrary to public opinion it has not completely solved the protein folding problem. Much work remains to be done.
clauswilke.substack.com/p/no-alphafo...
No, AlphaFold has not completely solved protein folding
Biology is hard. Yes, even for AI.
clauswilke.substack.com
July 12, 2025 at 6:19 PM
Reposted by GAMA Miguel Angel
glycojones.bsky.social
As the community gets ready for #ACA2025, we're proud to present this interview with @gabbygrowsxtals.bsky.social Vivian Stojanoff and @xtalmaker.bsky.social on how to prepare for successful protein crystallisation experiments! 🥳🥳 youtu.be/m34RI500OFU?...
Preparing for successful protein crystallization experiments
YouTube video by International Union of Crystallography
youtu.be
July 14, 2025 at 9:02 AM
Reposted by GAMA Miguel Angel
delalamo.xyz
This paper is absolutely bananas and a tour de force of structural bioinformatics. Some random tidbits:
jlsteenwyk.bsky.social 🧬Jacob L Steenwyk @jlsteenwyk.bsky.social · Jul 10
NEW pub: The role of metabolism in shaping #enzyme structures over 400 million years. Now out in @nature.com

Super grateful to have played a small role in this project - congrats to lead/corr authors Oliver, Benjamin, and Markus!

www.nature.com/articles/s41...

#alphafold #evolution #genomics
July 14, 2025 at 6:15 PM
Reposted by GAMA Miguel Angel
hansonmark.bsky.social
The "reproducibility crisis" in science constantly makes headlines. Repro efforts are often limited. What if you could assess reproducibility of an entire field?

That's what @brunolemaitre.bsky.social et al. have done. Fly immunity is highly replicable & offers lessons for #metascience

A 🧵 1/n
July 10, 2025 at 8:23 AM
Reposted by GAMA Miguel Angel
bioinfo.se
A paper thar took too long to finish. We show that AlphaFold3 its clearly better than AlphaFold2 (and Boltz-1 and Chai-1) to predict the structure of antibody-Antigens, but only for cases with (har to detect) similarity in the training set.

www.biorxiv.org/content/10.1...
Evaluating Deep Learning Based Structure Prediction Methods on Antibody-Antigen Complexes
Motivation: AlphaFold2 significantly improved the prediction of protein complex structures. However, its accuracy is lower for interactions without co-evolutionary signals, such as host-pathogen and a...
www.biorxiv.org
July 12, 2025 at 2:13 AM
Reposted by GAMA Miguel Angel
carlbergstrom.com
1. Kevin Gross and I just posted a new science-of-science preprint.

This one explores the looming peer review crisis. As many of you know, it's becoming significantly more difficult for journal editors to find scholars willing to serve as peer reviewers for submitted manuscripts.
Will anyone review this paper? Screening, sorting, and the feedback cycles that imperil peer review
Scholarly publishing relies on peer review to identify the best science. Yet finding willing and qualified reviewers to evaluate manuscripts has become an increasingly challenging task, possibly even ...
arxiv.org
July 16, 2025 at 3:13 AM
Reposted by GAMA Miguel Angel
alexis-verger.cpesr.fr
The Baker lab @uwproteindesign.bsky.social apparently had a lot of fun 😂

some examples of sequences used in the paper www.science.org/doi/10.1126/...

DAVIDLIKESPEPTIDE
DAVIDITISTIME
DANIELSILVA
HIALIENFRIEND
Design of intrinsically disordered region binding proteins
Intrinsically disordered proteins and peptides play key roles in biology, but a lack of defined structures and high variability in sequence and conformational preferences have made targeting such syst...
www.science.org
July 18, 2025 at 7:55 AM