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Our minimal MAP (i.e., microtubule associated protein) - the starPEG-KA7 peptide (see doi.org/10.1091/mbc.E19-05-024) is going places, er..., biomolecules🧬 !

New work by the Göpfrich (Heidelberg) and Kierfeld (Dortmund) labs shows that starPEG-KA7 deployed on DNA filaments facilitates the formation of DNA rings that are able to contract upon heat or molecular crowding cues:

nature.com/articles/s41467-024

#actinmyosin #synbio #artificialcell

@tsturm @sohkamyung I think if a giant clam posted, it would be something like:
Clam Log, shell growth line 12,601
Insolation optimal, photosynthetic output at maximum. Basking at maximum shell gape. Growing a new line for the day.
SOMETHING TOUCHED ME, CLOSE UP CLOSE UPPPP
False alarm.
Proceed with scheduled photosynthesis

In Memoriam

Bill Weis (1959–2023): Pioneering structural biologist and biochemist who revolutionized our understanding of cell adhesion and Wnt signaling

Obituary by Mark Peifer and Alexander R. Dunn published in @JCellBiol

t.co/WwIm1qhtme

Whenever I think someone is way too excited about fractals I zoom out a bit and find someone else even more excited...

Helping someone debug someone, said they asked chatgpt about what a series of bit shift operations were doing. He thought it was actually evaluating the code, yno like it presents itself as doing. Instead its example was a) not the code he put in, with b) incorrect annotations, and c) even more incorrect sample outputs. Has been doing this all day and had just started considering maybe chatGPT was wrong.

I was like first of all never do that again, and explained how chatGPT wasnt doing anything like what he thought it was doing. We spent 2 minutes isolating that code, printing out the bit string after each operation, and he immediately understood what was going on.

I fucking hate these LLMs. Empowerment is learning how to figure things out, how to make tools for yourself and how to debug problems. These things are worse than disempowering, teaching people to be dependent on something that teaches them bullshit.

@MCDuncanLab @cyrilpedia I disagree that it is solely about protecting companies from liability. The folks whose writing was used without consent to build the training corpus for ChatGPT have a legitimate interest in holding OpenAI accountable. I hope they succeed, and if so then I hope that publishers do the responsible thing and avoid liability. This is interest convergence!

@MCDuncanLab @cyrilpedia and as a human being I hate the thought of the “ChatGPTification” of our writing and communication styles. ChatGPT is wordy, bland, and lacking insight. It may be fine for mimicking corporate-speak in mundane emails, but I don’t want that anywhere near the creative and scholarly process of academic writing.

@MCDuncanLab @cyrilpedia we don’t allow plagiarism as a strategy to help convey our scientific discoveries more clearly. To me ChatGPT is much more similar to plagiarism than to hiring an editor—conflating the two ignores the fundamentally extractive and exploitative nature of how ChatGPT was built. Plus there is a real risk of plagiarizing with ChatGPT! Of course ChatGPT makes stuff up as you note, but it can also just spit out training data, aka other people’s words.

@MCDuncanLab @cyrilpedia I can think of lots of reasons not to let the Stochastic Parrot anywhere near the scientific publishing system. With all the litigation about copyright infringement by ChatGPT in their unethical scraping of the web, I can imagine editors would want to steer well clear of any futute legal issues, as do I!

@Co_Biologists “other”: Remote option for those that can't travel in a low carbon way would be great. I understand not always possible depending on the event or on the demand due to the cost.

Hello naparistas! We are proud/relieved to announce the release of napari 0.4.19! 🥳 Back in August @czaki was like, "I think we should make a quick bug-fix release post 0.4.18”… 6 months later… 😅 #FOSS #OpenSource

We fixed major, long-standing bugs with color handling in Labels layers, and improved performance — especially for (u)int8/16 data. It's also easier to create custom colormaps — see 1st pic which uses a variant of Glasbey. 😍

Check out the full release notes! napari.org/stable/release/rele

Moralizing QRPs without acknowledging or providing alternatives for our punishing reward / job / work system does not align with my personal values or the values of the academic system I want to be building.

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@aheadofthenerve realistically you are going to have to walk people through your data with those kind of heuristics anyway (what happens when input 1 increases for fixed input 2) so you might as well have the plots reflect that “narrative” structure

@aheadofthenerve your point about the 3D plot reveals that we’re just not good at perceiving all those relationships at the same time. I would break it down into multiple 2D plots, each with multiple curves: x is input 1, y is output 1 each curve a fixed value of input 2. Then have a side by side plot with x input 1, and y output 2.

I traveled to Paris to give my philosophy crash course for scientists (johannesjaeger.eu/philosophy.h) to a wonderful group of PhD students at LPI Paris, as I do every year.

Contact me if you want to bring this course to your own institute!

It's not only fun, but also useful allowing you to become a better researcher through philosophy. The course has an interactive, discussion-based format that is based on an online series of lecture which are freely available: youtu.be/EH3-9myS8qU?si=gGxiF0.

To celebrate the 40th anniversary of MBE, the SMBE journals will be publishing Perspectives and Virtual Issues each month highlighting our historic and contemporary contributions to a specific topic in molecular evolution. Read more in our first Perspective, written by the EiCs of both journals. doi.org/10.1093/molbev/msad264 #science #evolution #biology #genome #evolgen_paper

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