{"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/bayesian-neural-networks-for-genetic","title":"Bayesian Neural Networks for Genetic Association Studies of Complex Disease","arxiv_id":"1404.3989","date":"2014-04-15","proceeding":null,"authors":["Andrew L. Beam","Alison Motsinger-Reif","Jon Doyle"],"abstract":"Discovering causal genetic variants from large genetic association studies\nposes many difficult challenges. Assessing which genetic markers are involved\nin determining trait status is a computationally demanding task, especially in\nthe presence of gene-gene interactions. A non-parametric Bayesian approach in\nthe form of a Bayesian neural network is proposed for use in analyzing genetic\nassociation studies. Demonstrations on synthetic and real data reveal they are\nable to efficiently and accurately determine which variants are involved in\ndetermining case-control status. Using graphics processing units (GPUs) the\ntime needed to build these models is decreased by several orders of magnitude.\nIn comparison with commonly used approaches for detecting genetic interactions,\nBayesian neural networks perform very well across a broad spectrum of possible\ngenetic relationships while having the computational efficiency needed to\nhandle large datasets.","url_abs":"http://arxiv.org/abs/1404.3989v2","url_pdf":"http://arxiv.org/pdf/1404.3989v2.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":"bayesian-neural-networks-for-genetic","repo_url":"https://github.com/beamandrew/BNN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}