Aidan Tinafar • cell-free.com

712 posts

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Aidan Tinafar • cell-free.com

Aidan Tinafar • cell-free.com

@Tinafar

Making biology user-friendly #liberumbio #cell-free Ad vitam per naturam Opinions are my own

Katılım Ocak 2010
257 Takip Edilen5K Takipçiler
Aidan Tinafar • cell-free.com
@BrianRoemmele If you humanize something, please make it dignified. I think I would be okay with fetal position when unboxing a new humanoid robot, but open to ideas.
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Brian Roemmele
Brian Roemmele@BrianRoemmele·
This robot packing themselves in a suitcase gives me the ick.
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Avi Marcus
Avi Marcus@Avi_Marcus·
If you could design a biosensor for any small molecule or protein what would you target?
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Cyan Banister
Cyan Banister@cyantist·
Who are the best people in the world right now studying or writing about consciousness?
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Aidan Tinafar • cell-free.com
@josiezayner Depends on the subfield. Some areas are streamlined, but others require building your own infrastructure to make any progress. Unlike software, biology still lacks true abstraction layers - there’s very little ‘AWS for biology’ despite recent claims.
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Josie Zayner
Josie Zayner@josiezayner·
Is biotech really that hard to understand for those not in the industry?
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Rasmus Kirkegaard
Rasmus Kirkegaard@kirk3gaard·
Who is teaching sales departments that the best way to sell your products is to have people contact a person rather than just clicking buy? (I assume Amazon has the "Buy now" button for a reason...)
Rasmus Kirkegaard tweet media
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Aidan Tinafar • cell-free.com retweetledi
Massimo
Massimo@Rainmaker1973·
Single-cell manipulation with laser-powered microbots using elastic nanorods and laser tweezers. [🔬 Szeged Institute of Biophysics, Hungary]
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Aidan Tinafar • cell-free.com
@DdelAlamo Could it be that DNA they considered here is mostly in double-stranded form (~linear) and that RNA is most single-stranded and has complex secondary structure of its own?
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Diego del Alamo
Diego del Alamo@DdelAlamo·
What is it about protein-RNA structures that makes them so difficult to predict compared to protein-DNA structures? It genuinely looks like there is nothing to learn here. LDDT=0.25 is basically garbage
Diego del Alamo tweet media
Biology+AI Daily@BiologyAIDaily

SeedFold: Scaling Biomolecular Structure Prediction 1. SeedFold introduces an innovative approach to scaling biomolecular structure prediction models, achieving state-of-the-art performance on FoldBench. The model outperforms AlphaFold3 in multiple tasks, highlighting its potential for advancing structural biology and drug discovery. 2. The study proposes a novel linear triangular attention mechanism that reduces computational complexity from cubic to quadratic, enabling more efficient scaling. This innovation addresses the computational bottleneck of traditional triangular operations in folding models. 3. SeedFold explores different scaling strategies, finding that increasing the width of the Pairformer module is more effective than deepening the model. This width-scaling strategy significantly enhances the model's capacity to encode complex pairwise interactions. 4. A large-scale distillation dataset was constructed to expand the training set to 26.5 million samples. This approach leverages knowledge from AlphaFold2 to improve the generalization of SeedFold, especially for tasks with limited experimental data. 5. Experiments show that SeedFold excels in predicting protein monomers, antibody-antigen interactions, and protein-RNA interfaces, while its linear variant performs exceptionally well in protein-ligand interactions. This indicates the versatility of the model across various biomolecular tasks. 6. The training process includes a two-stage strategy and stability optimizations to handle the challenges of scaling large models. Techniques like extended warm-up periods and reduced learning rates ensure stable convergence during training. 📜Paper: arxiv.org/abs/2512.24354

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Brian Roemmele
Brian Roemmele@BrianRoemmele·
Send in the drone! Solar panels get dusty. This drone can clean it. Results in more efficiency pays for the drone 2x.
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Aidan Tinafar • cell-free.com retweetledi
Massimo
Massimo@Rainmaker1973·
Before and after footage showing the improvement made by Gath, a Parkinson's patient after just two days on a new drug Produodopa treatment, after being diagnosed 12 years ago.
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cinesthetic.
cinesthetic.@TheCinesthetic·
What’s the one foreign-language film you’d recommend to someone who only watches English movies?
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Kevin K. Yang 楊凱筌
Kevin K. Yang 楊凱筌@KevinKaichuang·
I need a wetlab so that I can screen my submissions to protein design competitions before submitting
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Aidan Tinafar • cell-free.com
@NikoMcCarty You can just use synthesized linear DNA in cell-free. There is no need for cloning. Folding issues are not unique to cell-free systems. Some sequences just don't fold as well as others and/or are less soluble.
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Niko McCarty.
Niko McCarty.@NikoMcCarty·
How far are we from "protein printers" that enable anyone to make a protein of any sequence on-demand in a couple hours? I'm imagining a box that takes a protein design from a computer and then physically makes it on a bench or desk. This isn't yet feasible. It's still expensive and tedious to make proteins. There are many steps involved. But there are two main ways to make a protein: 1. Order a DNA sequence encoding the protein of interest. Clone the DNA and insert it into a cell-free extract, microbe or other cell line. Coax the cell to make the protein, then purify it. (There is no guarantee that the DNA sequence will even be expressed! And if it is, no guarantee that the protein will fold as anticipated.) 2. Do peptide synthesis. Chemically assemble amino acids into longer chains. The problem here is that there is a particular efficiency of each step, and so it becomes less and less efficient to make longer proteins. A protein printer could work by miniaturizing and automating option #1. Imagine if DNA synthesis costs were significantly cheaper, and if that DNA could be quickly made on-demand. Then, one could make a Protein Printer by hooking up a DNA synthesis box to a PCR machine to a pipetting robot, etc. But I think a better option is to forego #1 and #2 entirely, and find a new way to make proteins. I previously co-wrote an essay on one such approach, in which we imagined a rotary telephone in which all the different codons — AUA, AUG, AUC, and so on — are placed on a single, continuous loop of RNA. The ribosome would then be engineered to ‘hop’ from one codon to the next to build custom proteins (with no DNA synthesis required!). The difficult part of this idea is that there are no good ways to controllably coax ribosomes to hop between codons reliably and at high speeds. The idea was widely criticized, even as some readers told me that they are working on similar ideas. I don't know what a Protein Printer in the future will look like, but I do think it's an important thing to work towards. It would facilitate the democratization of education and local biomanufacturing that I've long dreamt of. There would be biosecurity concerns, of course, but those same concerns also apply to DNA printers (which are already available on the market), and there are ways to safely screen proteins before they get manufactured. For decades, people have argued that "biotechnology is not like computer science." The latter can be done in quick, iterative loops; the former is slow and tedious. A protein printer would help shift this equation, enabling far more people to experiment. Perhaps in the future, people could print their own medicines or vaccines at home. The hit rate of our AI design tools is also improving so rapidly that the need for validating protein designs before they are made will recede. Protein binder design went from a <1% hit rate to rates now closer to 22% or more. I think this "on-demand" protein idea is worth thinking about.
Niko McCarty. tweet media
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Ivan Zhang
Ivan Zhang@1vnzh·
weight of the world feels lighter when I see my customers smile
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Aidan Tinafar • cell-free.com
@TheHubCanada @harleyf @Shopify Spinning up stories is just not enough. Canada needs to have QSBS equivalents and favourable share disposition rules for founders. Grants need to relax their IP domicile restrictions. Companies should have the option to obtain pre-approvals on customs clearances for all exports.
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The Hub
The Hub@TheHubCanada·
‘We need to reframe our story to focus on what’s possible’: Shopify President @harleyf on how Canada can become a ‘Founder Nation’ This episode was made possible by @Shopify and the generosity of viewers like you. thehub.ca/podcast/video/…
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