erva

🚀 Exciting news! Our project, CROssBARv2, is now live as an online tool and its article (preprint)! We've built a unified AI-powered platform that brings together the fragmented world of biomedical data — and lets you talk to it in plain English. Here's the story 👇 The problem, in plain terms: Imagine being a detective, but your clues are scattered across 34 different filing cabinets, written in different languages, with no index. That's what biomedical researchers face every day — genes in one database, drugs in another, diseases somewhere else. Connecting the dots is slow & painful without serious programming skills. CROssBARv2 is our answer to this. 🧬💊🔬 What did we build? CROssBARv2 is a biomedical Knowledge Graph (KG) — think of it as a giant, intelligent map of biology. We integrated data from 34 well-established databases into a single, structured, and searchable system: 🔵 ~2.7 million nodes (proteins, genes, drugs, diseases, pathways, side effects, & more) 🔗 ~12.6 million edges (biomedical relationships) 🧠 14 node & 51 edge types 🏷️ Rich metadata Now the exciting part 🤖 — meet CROssBAR-LLM Large Language Models (LLMs) like ChatGPT or Gemini are brilliant at conversation — but they hallucinate. They confidently tell you things that sound right but aren't. In biomedicine, that's dangerous. Our solution: ground the LLM in the knowledge graph. CROssBAR-LLM lets you ask complex biomedical questions in plain English, like: "What proteins are encoded by genes regulated by NFKB1, participate in the Endocytosis pathway, and are targeted by drugs used to treat diseases comorbid with osteoporosis?" CROssBAR-LLM tutorial: youtu.be/FjuoKAmzjNM What happens under the hood: 🗣️ Your natural language question is translated into a formal DB query ⚡ The query runs on the CROssBARv2 KG in real time 📊 Structured, verified results are retrieved 💬 The LLM turns results into a clear, readable answer No hallucinations. Every answer is traceable back to real data How does it compare to just directly asking LLMs on a biomedical Q&A benchmark? GPT/Claude/Gemini: ~50-65% CROssBAR-LLM (w/ Gemini 1.5 Pro): 98% accuracy 🎯 CROssBAR-LLM (w/ GPT-4o): 97% accuracy 🎯 Everything is open and accessible 🔓 🌐 Web platform: crossbarv2.hubiodatalab.com 📡 GraphQL API 🖥️ Neo4j Browser for visualisation 📂 Full data on Hugging Face & Google Drive 💻 All code on GitHub No paywall. No programming required. Just ask your question! Huge thanks to the team! Bünyamin Şen, Erva Ulusoy @ervaulusy , Melih Darcan, Mert Ergun, Sebastian Lobentanzer, Ahmet S. Rifaioğlu @ahmet_rifaioglu , Dénes Türei, Julio Saez Rodriguez @JulioSaezRod , and me, in collaboration with Saez Lab @saezlab spanning Hacettepe University @Hacettepe1967 , Heidelberg University @HeidelbergU , Helmholtz Munich @HelmholtzMunich , and European Bioinformatics Institute | EMBL-EBI @emblebi 📄 Read the preprint: biorxiv.org/content/10.648… ⚙️Try the tool: crossbarv2.hubiodatalab.com/llm ***Please repost!*** #AI #LLM #ML #Bioinformatics #KnowledgeGraph #DrugDiscovery #Biomedicine #OpenScience

🚀 Our new book chapter is out in Protein Function Prediction: Methods and Protocols: “A Benchmarking Platform for Assessing Protein Language Models on Function-Related Prediction Tasks” link.springer.com/protocol/10.10… w/ @elif_cevrim @mgyigit @ervaulusy & Ardan Yılmaz ++

Hacettepe Biological Data Science Lab is on site at #ISMBECCB2025 (20–24 July, ACC Liverpool)—the flagship bioinformatics forum uniting ISMB & ECCB. The atmosphere is truly inspiring and dynamic. 🔬✨ #bioinformatics ++

Erva Ulusoy @ervaulusy is on stage presenting ProtHGT—heterogeneous graph transformers + protein LMs for protein‑function prediction with biological knowledge graphs— on the #Function stage at #ISMBECCB2025

Excited to share our new article 🚨 “Protein Language Models for Predicting Drug–Target Interactions: Novel Approaches, Emerging Methods & Future Directions” with @atabeyunlu @ervaulusy @mgyigit & Melih Darcan is published in COSTBI Free access link: authors.elsevier.com/a/1keXR,LqArXq…

New article 📢 Our study entitled: "Mutual annotation-based prediction of protein domain functions with Domain2GO" with @ervaulusy is now published in the Protein Science journal onlinelibrary.wiley.com/doi/10.1002/pr… 🧬🤟🎊 #ProteinScience @ProteinSociety onlinelibrary.wiley.com/journal/146989… ++

Great new work by @ervaulusy @atabeyunlu @tuncadogan et al @hubmb @ai_hacettepe @hubioinf @HUbilisim -'SELFormer: molecular representation learning via #SELFIES language models'- bit.ly/3Ny2aod #machinelearning #compchem #drugdiscovery #AI #materials #bioinformatics #NLP

New paper alert 🚨 I'm happy to announce that our collaborative project led by @slobentanzer & @JulioSaezRod @saezlab on developing an #opensource framework called "BioCypher" for easy creation & manipulation of biological knowledge graphs has been published @NatureBiotech 🥳

Aynı haftada grubumuzdan bir güzel haber daha 🚨 Erva "Heterojen Biyomedikal Verinin Bilgi Çizgeleri ve Derin Öğrenme Tabanlı Analizi ile Protein Fonksiyonlarının Otomatik Tahmini" başlıklı yüksek lisans (YL) tezini başarı ile savundu Tebrikler @ervaulusy 👏🥳🤟 Beklenen ++

Good news from our lab 🚨 All of our submissions got accepted (4 oral, 3 posters) at the flagship bioinformatics conference, ISMB/ECCB2023 iscb.org/ismbeccb2023 Congrats to all, starting from presenters: @ervaulusy @atabeyunlu @serbulentunsal Burakcan, Elif & @heval_atas 1/6

New paper 🚨🤟🥳🎸 "SELFormer: Molecular Representation Learning via SELFIES Language Models" is out as a pre-print arxiv.org/abs/2304.04662 Started as an undergraduate course project and evolved into a new chemical language model! #DeepLearning #DrugDiscovery #ML #AI 1/8

Teyzem göçük altında... Lütfen yardım edin! Nihal Rifaioğlu HATAY ANTAKYA akevler mah 432. Sok torunlar apt bedi sabuncu ortaokul yanı 0 (555) 156 31 10 (kardeşi) @AFADHatay @AFAD_Ankara @ahbap @haluklevent @OguzhanUgur

Building a knowledge graph for biomedical tasks usually takes months or years. 😰 What if you could do it in weeks or days? 🏃 We created BioCypher (biocypher.org) to make it easier than ever, but still flexible and transparent. 🧵⬇️

Two days full of exciting science #HIBIT2022 Turkish bioinformatics community rocks 🤟🏼 Thanks to organizers @yaydinson Dr Arzu Karahan @BurcakOtlu also @RSGTurkey & all students who worked tirelessly Love from Hacettepe Biological Data Science Lab, hope to see you all next year

@animaIarmy çözümü ekranın yarısını kuş videolarına ayırmakta buldum

@umayecek dlcleri crackli indirip orijinal oyuna entegre edebilirsiniz 😇

Kendine hakim ol Ece’cim. Kendine hakim ol Ece’cim

Mesai biter, diger mesai baslar

AI tool to generate colour palettes from any text prompt — #stablediffusion #ArtificialIntelligence

I don’t need ketamine therapy I need a walkable city and 20 hour workweek

@prudentias i told you 😇

WAIT they meant Nishinoya when they were talking about ‘guardian angel’???? i mistook that as Asahi,,,,okay my favorite might change 👀

i’m finally watching haikyuu and even though Asahi is not here yet i KNOW he is going to be my favorite character