--- title: Implementation of Graph Neural Networks in drug... description: Serokell AI experts developed graph neural network models to predict drug-disease interactions using data from Elsevier. The project involved two main tasks:... canonical: https://daily.dev/posts/implementation-of-graph-neural-networks-in-drug-discovery-research-m4tvvd6qx twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Implementation of Graph Neural Networks in drug discovery research | daily.dev og:description: Serokell AI experts developed graph neural network models to predict drug-disease interactions using data from Elsevier. The project involved two main tasks:... og:url: https://daily.dev/posts/implementation-of-graph-neural-networks-in-drug-discovery-research-m4tvvd6qx og:image: https://api.daily.dev/og/posts/M4tVVD6Qx.png og:image:alt: Implementation of Graph Neural Networks in drug discovery research og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Implementation of Graph Neural Networks in drug discovery research **[Serokell](https://daily.dev/sources/serokell)** · 10 min read · 0 upvotes · 0 comments ## Summary Serokell AI experts developed graph neural network models to predict drug-disease interactions using data from Elsevier. The project involved two main tasks: predicting interactions between drugs and diseases using heterogeneous graph structures with 10 node types and 158 edge types, and biological sequence embedding to compress DNA and amino acid sequences. The team migrated from TensorFlow to PyTorch Geometric to better handle the complex graph data, implementing separate embedding models for each node type and unique GNNs for each edge type. The approach uses message passing and graph convolutions to capture relationships in the biological data, with future work planned on larger datasets and paralog-type connections for drug repurposing. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [A Deeper Dive into Graph Neural Networks](https://daily.dev/posts/a-deeper-dive-into-graph-neural-networks-bjxzik1ur) · DigitalOcean Community · 0 upvotes · 0 comments - [Agentic AI framework in life sciences for R&D](https://daily.dev/posts/agentic-ai-framework-in-life-sciences-for-r-d-vcvbbbffj) · Google Cloud · 0 upvotes · 0 comments - [Why Life Sciences AI Is a Search Problem \(Part 2 of 5\)](https://daily.dev/posts/why-life-sciences-ai-is-a-search-problem-part-2-of-5--igp5g1mmo) · Vespa Blog · 0 upvotes · 0 comments - [Building AI models that understand chemical principles](https://daily.dev/posts/building-ai-models-that-understand-chemical-principles-lqfou62pp) · MIT News · 2 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#deep-learning](https://daily.dev/tags/deep-learning), [#pytorch](https://daily.dev/tags/pytorch), [#biotech](https://daily.dev/tags/biotech) [View this post on daily.dev](https://daily.dev/posts/implementation-of-graph-neural-networks-in-drug-discovery-research-m4tvvd6qx) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Implementation of Graph Neural Networks in drug discovery research","url":"https://daily.dev/posts/implementation-of-graph-neural-networks-in-drug-discovery-research-m4tvvd6qx","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/implementation-of-graph-neural-networks-in-drug-discovery-research-m4tvvd6qx"},"datePublished":"2026-02-04T12:53:51.031Z","dateModified":"2026-02-04T12:54:35.100Z","description":"Serokell AI experts developed graph neural network models to predict drug-disease interactions using data from Elsevier. 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