Axy
@axy-app.bsky.social
Every scientist thinks in knowledge graphs — we're making them visible. Axy maps research at the level of ideas, not citations, so a lab's understanding becomes something the community can inherit and build on. Here to think out loud with researchers.
PubMed Knowledge Graph 2.0 just linked 36M+ papers, 1.3M patents, and 480K+ clinical trials into one graph. A gene-disease finding from 2012 → a 2015 patent → a 2019 trial can be traced as a single path. That kind of infrastructure didn't really exist before.
We made a list of research tools that can actually save your time in academics, and no, that's not another 50-app roundup. Research Rabbit for literature discovery (free, visual, syncs with Zotero). Overleaf for LaTeX co-authoring. Get an ORCID if you still don't have one. 🧵
Before 2007: a fish list from the North Atlantic and a mollusc catalogue from the Mediterranean could disagree on the name for the same organism, with no shared identifier to reconcile them. WoRMS closed that gap. 🧵
You hit Figure 3 in a paper: a tangle of coloured dots joined by arrows pointing every direction. Caption just says "knowledge graph." You read the rest fine but this one figure stops you. It's not you. Nobody taught you the grammar. 🧵
DGL and PyTorch Geometric were both born in 2019. DGL's bet: treat the graph itself as the core abstraction , framework-neutral across PyTorch, TensorFlow, and MXNet rather than bolting sparse tensors onto an existing dense-tensor framework. 🧵
GBIF has 2.8 billion occurrence records across 10 million species from 1,600+ institutions in 197 countries. That still doesn't make it a random sample of life on Earth, and treating it like one has gotten papers published that didn't survive scrutiny. 🧵
Every knowledge graph whether GBIF for biodiversity, Monarch for gene-disease links, PubMed KG for the literature gets rebuilt in isolation. Connecting two of them by hand still takes ~2 weeks. That's the exact seam AI is now stitching. 🧵
You spend weeks on Google Scholar, Connected Papers, bioRxiv, conference abstracts - then hit a 15-year-old paper (sometimes in another language) that already tested your exact idea. That's not a research productivity problem. It's an infrastructure gap in science. 🧵
Trying to find relevant posters/talks at #Europar2025 ? 🧵 Forget the older methods 📚😵💫 We built Axy because WE were missing relevant research at conferences ✨ beta.axy-app.com/europar2025 🔥 Pro tip: Search for a couple papers you love → add to agenda → watch the recommender work its magic
Trying to find relevant posters/talks at #ICML2025 🧵 Forget Whova 📚😵💫 We built Axy because WE were missing relevant research at conferences ✨ beta.axy-app.com/icml2025/home 🔥 Pro tip: Search for a couple papers you love → add to agenda → watch the recommender work its magic
