Summary of Scalable Knowledge Graph Construction and Inference on Human Genome Variants, by Shivika Prasanna et al.
Scalable Knowledge Graph Construction and Inference on Human Genome Variants
by Shivika Prasanna, Deepthi Rao, Eduardo Simoes, Praveen Rao
First submitted to arxiv on: 7 Dec 2023
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Databases (cs.DB); Quantitative Methods (q-bio.QM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to representing real-world genomic data, specifically RNA-sequencing information from COVID-19 patients, as a unified knowledge graph. The authors use variant call format (VCF) files and annotate them with additional information, then convert the data into Resource Description Framework (RDF) triples. They define an ontology for the VCF and CADD scores files and leverage available storage to create a large-scale knowledge graph. This enables querying and creating datasets for further downstream tasks. The authors also demonstrate the effectiveness of this approach by performing a classification task using graph machine learning and comparing different Graph Neural Networks (GNNs). Keywords: knowledge graph, RNA-sequencing, COVID-19, variant call format, Resource Description Framework, ontology, graph machine learning, Graph Neural Networks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine if you could turn complex genomic data into a map that makes sense. That’s what this paper does! They take information from COVID-19 patients and create a big picture called a knowledge graph. This helps them find patterns and make predictions about the data. The authors use special tools to organize the data and then test their approach by doing a specific task. They show that their method works well using different techniques, which is important for understanding genomic data. |
Keywords
* Artificial intelligence * Classification * Knowledge graph * Machine learning
