{"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/magan-aligning-biological-manifolds","title":"MAGAN: Aligning Biological Manifolds","arxiv_id":"1803.00385","date":"2018-02-10","proceeding":"ICML 2018 7","authors":["Matthew Amodio","Smita Krishnaswamy"],"abstract":"It is increasingly common in many types of natural and physical systems\n(especially biological systems) to have different types of measurements\nperformed on the same underlying system. In such settings, it is important to\nalign the manifolds arising from each measurement in order to integrate such\ndata and gain an improved picture of the system. We tackle this problem using\ngenerative adversarial networks (GANs). Recently, GANs have been utilized to\ntry to find correspondences between sets of samples. However, these GANs are\nnot explicitly designed for proper alignment of manifolds. We present a new GAN\ncalled the Manifold-Aligning GAN (MAGAN) that aligns two manifolds such that\nrelated points in each measurement space are aligned together. We demonstrate\napplications of MAGAN in single-cell biology in integrating two different\nmeasurement types together. In our demonstrated examples, cells from the same\ntissue are measured with both genomic (single-cell RNA-sequencing) and\nproteomic (mass cytometry) technologies. We show that the MAGAN successfully\naligns them such that known correlations between measured markers are improved\ncompared to other recently proposed models.","url_abs":"http://arxiv.org/abs/1803.00385v1","url_pdf":"http://arxiv.org/pdf/1803.00385v1.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":"magan-aligning-biological-manifolds","repo_url":"https://github.com/KrishnaswamyLab/MAGAN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1803.00385","atlas_url":"https://app.syntology.ai/?focus=1803.00385","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}