SeqHub MSA live, integrated with structure vis! Another user requested feature🤝

We’re incredibly grateful to have Alex Bateman on our advisory board. Biology today would look very different without UniProt. Scientific data infrastructure is the bedrock of innovation, and we’re excited to learn from Alex’s experience helping building such a foundational resource.

Most protein-protein interaction tools work on protein pairs. FlashPPI runs at proteome scale and now across two proteomes at once. Upload any two datasets (full genomes, partial genomes, or custom protein sets) and get back a predicted interaction network spanning both.

We're hosting a live walkthrough of FlashPPI in SeqHub on April 15 at 11am EST. We'll briefly discuss our protein-protein interaction model then walk through how you can use it in SeqHub. Register here: forms.gle/iBQrpYnLeiF1...

My group at MIT is seeking a research scientist with a strong *experimental* background to lead and help shape the lab’s experimental infrastructure, supporting efforts to advance AI-driven enzyme discovery and characterization. See the full JD here: acrobat.adobe.com/id/urn:aaid:...

Applications for MIT Novo-Nordisk AI postdoc fellowships are due Apr 15. Focus area lists AI and Biology topics, apply to work on this exciting field with amazing peers! engineering.mit.edu/novo-nordisk

We thought a lot about how to deploy 𝑭𝒍𝒂𝒔𝒉𝑷𝑷𝑰, and we are very proud of this implementation that integrates annotation+context+CoSearch+agent with FlashPPI on SeqHub!

Step-by-step how to run FlashPPI on your favorite genomes!

Predicting protein-protein interactions (PPIs) at proteome scale can take months with co-folding models due to the massive all-vs-all comparisons required. We are excited to announce FlashPPI, a contrastive learning framework that predicts proteome wide physical interfaces in minutes. 1/🧵

Protein–protein interactions (PPIs) are key to discovering and interpreting new biological functions. We’re excited to introduce 𝑭𝒍𝒂𝒔𝒉𝑷𝑷𝑰: a new application of gLM2 that uses genomic language modeling to predict proteome-wide PPIs in microbial genomes in minutes.

We’d love to join your lab meeting! We’ve been meeting with research groups to share how scientists are using SeqHub for sequence and genome analysis, and the conversations have been highly interactive and grounded in real workflows. Booking info below.

We’re excited to welcome Daniela Bourges-Waldegg to the SeqHub Advisory Board! Daniela is EVP + Chief Digital & Technology Officer at @addgene.bsky.social. She will help shape our approach to building researcher-centered digital infrastructure with an eye toward long-term scientific impact.

First, @tattabio.bsky.social is now on Bluesky!💙 and second, we launched mult-sequence CoSearch on SeqHub!

This. Is. So. Cool. 🤯

Released today from Tatta Bio: SeqHub! A place to explore, annotate, and share sequence data with functional insights.  Over 1,000 scientists worldwide have already used SeqHub to annotate more than 550,000 proteins, uncovering new insights and accelerating discovery.

We're thrilled to announce SeqHub, an AI-enabled platform for biological sequence analysis. SeqHub brings together sequence search, genome annotation, and data sharing in one place.

Ready to explore New Lineages of Life with @jgi.doe.gov ? 🧬🦠 Registration for our 2025 NeLLi Symposium is now open. For the first time in collaboration with @unlv.edu Mark the date: November 6-7 in Las Vegas, NV

At Tatta Bio, we have been thinking deeply about the sequence-to-function problem. We believe that before AI can power functional prediction, we first need to rethink how we curate, manage, and share sequence data. Here, we share our initial ideas on what we are building next:

I am very happy (and anxious) to share with you our most recent work in which we evaluated four of the most popular long-read assemblers, www.biorxiv.org/content/10.1... and tell you just a little bit about it in the following 🧵

It’s official! 🎉 I’m thrilled to announce that I will be joining MIT as an assistant professor in a shared appointment between Biology, EECS and Schwarzman College of Computing this fall.

Tatta Bio is growing! We are hiring *two positions* in Business Development and Software Engineering to lead the development of AI-enabled scientific software for open science and biological sequence interpretation. Please check out the job postings at www.tatta.bio/careers and share widely!

Can LLM agents discover novel protein functions? Introducing Gaia Agent 🌎 🤖: an AI biologist capable of reasoning across genomic contexts to predict functions of proteins! Gaia Agent is now integrated with Gaia Search at gaia.tatta.bio

If you are at #NeurIPS2024 don't miss @ancornman1.bsky.social's talk on OMG/gLM2 at 9AM! @workshopmlsb.bsky.social East meeting room 11,12

Excited to be at #NeurIPS this week. @ancornman1.bsky.social will give a spotlight talk at the @workshopmlsb.bsky.social on gLM2/OMG! Please reach out if you want to chat about gLM2/OMG/Gaia and our latest projects😇 www.biorxiv.org/content/10.1...

Are you working on natural products? We’ve just released version 4.0 of the MIBiG data standard and repository! It now includes 3059 biosynthetic gene clusters, thanks to the combined efforts of 288 expert contributors. A thread: (1/8) academic.oup.com/nar/advance-...

1/🧬 Excited to share PLAID, our new approach for co-generating sequence and all-atom protein structures by sampling from the latent space of ESMFold. This requires only sequences during training, which unlocks more data and annotations: bit.ly/plaid-proteins 🧵

Our Big Fantastic Virus Database (BFVD) is now published NAR! It contains protein structure predictions of major viral clades, enhanced by petabase-scale homology search and it's explorable on the web. 🌐 bfvd.foldseek.com 💾 bfvd.steineggerlab.workers.dev 📄 academic.oup.com/nar/advance-...

Hello 🦋 #protein / #microbio / #BioML community! We are excited to release Gaia🌎, a context-aware protein search tool, extending protein search and discovery capabilities beyond sequence and structure, to include *genomic context*. Search your favorite protein sequences with on gaia.tatta.bio