AlphaGenome is out! Input 1 Mb DNA -> predict gene expression, transcription initiation, chromatin accessibility, histone modifications, transcription factor binding, chromatin contact maps, ..., up to single-base-pair resolution! Trained on human and mouse data 🧪🧬🖥️🦠✨
www.nature.com/articles/s41...
Bacteria may be engineered to learn, but natural evolution rarely favors this.
Protein-based memory inside a cell is metabolically expensive and dilutes quickly.
Instead, cells may rely on simpler probabilistic strategies like bet hedging, so no memory is required.
#MEvoSky #evobio ⚙️🧫🧠🧬
Loving those Goodsell-style protein illustrations! And cool circuits in the figures too
What kinds of cognitions are possible? Are there discrete classes of cognition? Here's our new paper with @brigan.bsky.social @jordiplam.bsky.social @mitibennett.bsky.social @mkhochb.bsky.social and @drmichaellevin.bsky.social arxiv.org/abs/2601.12837 We explore basal, neural and human-AI spaces.
If you are looking to integrate your latest genetic creation into the genome of your favourite bug, you might find our latest review now out in OUP Synthetic Biology useful. 🧬⚒️ Work led by Riesa Rohmat with input from Thea Irvine and Shivang Joshi. #genome #synbio doi.org/10.1093/synb...
Circadian rhythms as a modulator of gut microbiota-tumor microenvironment crosstalk
review in Cellular and Molecular Life Sciences
link.springer.com/article/10.1...
#ChronoSky #ChronoMicrobiology
If you ever post/publish about that, I'll be eager to read it!
Apparently an engineering issue with Springer Nature platform is inflating citations for their online journal articles through circular citation links. They were informed by the preprint authors months ago, but nothing's happened so far.
🧪
arxiv.org/abs/2511.01675
Very interesting!
Do you think this framework could be tweaked to work for ants–pheromones too? As they've also been shown to "solve" the shortest path problem in a "ring", at least in laboratory conditions.
Love that the preprint for that is already online!!
How “intelligent” is a slime mold? When it solves mazes, it might not be thinking:it’s obeying physics. Our new paper with
@jordiplam.bsky.social shows how it follows a least action principle,letting physics do the job arxiv.org/pdf/2511.08531
@drmichaellevin.bsky.social @docteur-drey.bsky.social
Sunday morining at @sfiscience.bsky.social
Just finished reading this and prefect timing, another cool Physarum preprint just went live. You may find it interesting:
'Cognition as least action: the Physarum Lagrangian'
arxiv.org/abs/2511.08531
New preprint:
arxiv.org/abs/2510.19976
"Morphological computational capacity of Physarum polycephalum"
Suyash Bajpai, Aviva Lucas-DeMott, @msahsorin.bsky.social, Philip Kurian
If you're a #teacher interested in a great #openaccess write up on reading #phylogenetic trees, check out www.digitalatlasofancientlife.org/learn/system... created by @jonhendricks.bsky.social and Elizabeth Hermsen.
Does a cell have a 'mind' - say a proto-mind or basal cognition? Although it was once a fringe idea, recent experimental and mathematical works are accumulating in its support. Here is an interesting recent work: www.biorxiv.org/content/10.1... #complexsystem #systemsbiology #sysbio
fans of T4P pili (and 'pili pili') take note 👇
#MicroSky
How can biological systems anticipate future events? In our new paper with @jordiplam.bsky.social, we show how a simple genetic circuit can predict future trends through a simple (and perhaps widespread) mechanism @drmichaellevin.bsky.social @koseskalab.bsky.social www.biorxiv.org/content/10.1...
Bacterial two-hybrid systems evolved: innovations for protein-protein interaction research
#MicroSky 🦠
The landscape of microbial associations in human cancer www.science.org/doi/10.1126/...
TLDR -- most cancers do not have microbiomes...but a few do have consistent microbe associations (i.e., colorectal and oral cancers). Make sense!
Looks interesting: fluorescent proteins being strung together in a fiber as a recording of transcriptional history in cells.
Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues.
Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).
Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.
Protecting the Ecosystem of Human Knowledge: Five Principles
Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...
We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
1/n
Synthetic promoters has relied on naturally occurring TFs or Cas9. With de novo designed DNA binding proteins, there are so much potential for synbio, whether it's targeting natural promoters or designing synthetic ones.
Can engineered genetic circuits reveal principles and constraints of biological cognition?
🧬🦠🖥️ #synbio #systemsbiology #cognition
How many chromosomes can an animal have?
In our paper out now in @currentbiology.bsky.social we show that the Atlas blue butterfly has 229 chromosome pairs- the highest in diploid Metazoa! These arose by rapid autosome fragmentation while sex chromosomes stayed intact.
www.cell.com/current-biol...
Bio-desulfurization of fossil fuels has been a classic env biotech challenge for decades, but the field became stagnant for a while … until @pglekas.bsky.social et al leveraged SynBio tools to develop superior whole-cell catalysts enviromicro-journals.onlinelibrary.wiley.com/doi/10.1111/... 😱
This podcast explores TeselaGen software and its role in revolutionizing cell therapy research and development. Discover how this cutting-edge AI-powered platform helps scientists design, build, and optimize biological products:
www.youtube.com/watch?v=O9HE... #biotech #synbio #AI
