{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/shu-visualization-of-high-dimensional","title":"Shu: Visualization of high dimensional biological pathways","arxiv_id":"2304.07178","date":"2023-04-14","proceeding":null,"authors":["Jorge Carrasco Muriel","Nicholas Cowie","Marjan Mansouvar","Teddy Groves","Lars Keld Nielsen"],"abstract":"Summary: Shu is a visualization tool that integrates diverse data types into a metabolic map, with a focus on supporting multiple conditions and visualizing distributions. The goal is to provide a unified platform for handling the growing volume of multi-omics data, leveraging the metabolic maps developed by the metabolic modeling community. Additionally, shu offers a streamlined python API, based on the Grammar of Graphics, for easy integration with data pipelines. Availability and implementation: Freely available at https://github.com/biosustain/shu under MIT/Apache 2.0 license. Binaries are available in the release page of the repository and the web app is deployed at https://biosustain.github.io/shu.","url_abs":"https://arxiv.org/abs/2304.07178v1","url_pdf":"https://arxiv.org/pdf/2304.07178v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"shu-visualization-of-high-dimensional","repo_url":"https://github.com/biosustain/shu","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"shu-visualization-of-high-dimensional","repo_url":"https://github.com/biosustain/shu_case_studies","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}