Hi Roland, our servers are in the US, we explicitly state in our docs that we do not train models on private data, and the data is private to you only - unless intentionally made public (for publication/data sharing purposes)!

thanks for the feedback! We are working on making more of the platform exportable as figures😊

Thank you for the shoutout!

Annotations are mapped using embedding-based search, making it faster than most alignment-based search. HMM prediction speed-up comes from some optimization and parallelization :)

Thank you! and PaperBLAST team deserves a shoutout for the sequence-paper linkages

@ancornman1.bsky.social @sokrypton.org @pgirguis.bsky.social @alexbateman1.bsky.social @simrouxvirus.bsky.social @apcamargo.bsky.social

Currently, SeqHub is optimized for microbial protein and genome analysis. As we expand beyond microbial data, we'd love your feedback to help shape what comes next. I'm deeply grateful to our team at Tatta Bio, and to our collaborators and funders, for making this vision a reality. 🔗 seqhub.org

We are building this infrastructure for the scientific community, and we invite feedback and collaboration from researchers at every stage. We are grateful to
the Moore Foundation for their generous support in making this project possible. Stay tuned for more updates!

www.tatta.bio/gaia

I am so grateful for all the support I received from my mentors, colleagues and collaborators over the years: @pgirguis.bsky.social, @sokrypton.org, @simrouxvirus.bsky.social, @alexjprobst.bsky.social, @annedekas.bsky.social

It’s been an incredible journey building Tatta Bio with @ancornman1.bsky.social to advance AI infrastructure for biology, and I will continue to further our mission as chief scientist.

My lab will couple ML and high throughput experimentation to harness the remarkable functional diversity of microbial genomes. If you are excited about the intersection of AI and microbiology, please get in touch!

Our thoughts too! (stay tuned👀) 😉

As we improve Gaia Agent, we want to hear your feedback on the agent predictions. If you have suggestions on how we can increase its capabilities, please reach out! This was a major collaborative effort with @cong-ml.bsky.social , @joshuakravitz.com @nishantjha.org @ancornman1.bsky.social @Tatta Bio

We tested Gaia Agent's capabilities with hypothetical genes in Mycobeterium tuberculosis. In our blog, We detail our in silico validation of Gaia Agent-predicted membrane transporter and lanthipeptide biosynthesis loci that were uncharacterized despite decades of Mtb research. Read more:

Like a human biologist, Gaia Agent considers sequence, structure and genomic context to *think* about functions of novel genes, drastically accelerating our ability to predict functions of billions of unannotated proteins across the tree of life.