{"686843":{"#nid":"686843","#data":{"type":"news","title":"NSF Grant Funds Protein Research for Drug Discovery and Personalized Medicine","body":[{"value":"\u003Cp\u003EProteins, including antibodies, hemoglobin, and insulin, power nearly every vital aspect of life. Breakthroughs in protein research are producing vaccines, resilient crops, bioenergy sources, and other innovative technologies.\u003C\/p\u003E\u003Cp\u003EDespite their importance, most of what scientists know about proteins only comes from a small sample size. This stands in the way of fully understanding how most proteins work and unlocking their full potential.\u003C\/p\u003E\u003Cp\u003EGeorgia Tech\u2019s \u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~yunan\/\u0022\u003EYunan Luo\u003C\/a\u003E believes artificial intelligence (AI) could fill this knowledge gap. The National Science Foundation agrees. Luo is the recipient of an NSF Faculty Early Career Development (\u003Ca href=\u0022https:\/\/www.nsf.gov\/funding\/opportunities\/career-faculty-early-career-development-program\u0022\u003ECAREER\u003C\/a\u003E) award.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cSo much of biology depends on knowing what proteins do, but decades of research have concentrated on a relatively small set of well-studied proteins. This imbalance in scientific attention leads to a distorted view of the biological landscape that\u0026nbsp;quietly shapes our data and our algorithms,\u201d Luo said.\u003C\/p\u003E\u003Cp\u003E\u201cMy group\u2019s goal is to build machine learning (ML) models that actively close this gap by generating trustworthy\u0026nbsp;function predictions for the many proteins that remain understudied.\u201d\u003C\/p\u003E\u003Cp\u003E[Related: \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/news\/faculty-use-ai-protein-design-and-discovery-support-18-million-nih-grant\u0022\u003EYunan Luo to use AI for Protein Design and Discovery with Support of $1.8 Million NIH Grant\u003C\/a\u003E]\u003C\/p\u003E\u003Cp\u003EIn his \u003Ca href=\u0022https:\/\/www.nsf.gov\/awardsearch\/show-award\/?AWD_ID=2442063\u0026amp;HistoricalAwards=false\u0022\u003Eproposal to NSF\u003C\/a\u003E, Luo coined this rich-get-richer effect \u201cannotation inequality.\u201d\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EOne problem of annotation inequality is that it slows progress in disease prognosis, drug discovery, and other critical biomedical areas. It is challenging to innovate the few proteins that scientists already know so much about.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EA cascading effect of annotation inequality is that it diminishes the effectiveness of studying proteins with\u0026nbsp;AI. \u0026nbsp;\u003C\/p\u003E\u003Cp\u003EAI methods learn from existing experimental data. Datasets skewed toward well-known proteins propagate and become entrenched in models. Over time, this makes it harder for computers to research understudied proteins.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cProtein annotation inequality creates an effect analogous to a vast library where 95% of patrons only read the top 5% popular books, leaving the rest of the collection to gather dust,\u201d Luo said.\u003C\/p\u003E\u003Cp\u003E\u201cThis has resulted in knowledge disparities across proteins in current literature and databases, biasing our understanding of protein functions.\u201d\u003C\/p\u003E\u003Cp\u003EThe NSF CAREER award will fund Luo with over $770,000 for the next five years to tackle head-on the problem of protein annotation inequality.\u003C\/p\u003E\u003Cp\u003ELuo will use the grant to build an accurate, unbiased protein function prediction framework at scale. His project aims to:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EReveal how annotation inequality affects protein function prediction systems\u003C\/li\u003E\u003Cli\u003ECreate ML techniques suited for biological data, which is often noisy, incomplete, and imbalanced \u0026nbsp;\u003C\/li\u003E\u003Cli\u003EIntegrate data and ML models into a scalable framework to accelerate discoveries involving understudied proteins\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EMore enduring than the ML framework, Luo will leverage the NSF award to support educational and outreach programs. His goal is to groom the next generation of researchers to study other challenges in computational biology, not just the annotation inequality problem.\u003C\/p\u003E\u003Cp\u003ELuo teaches graduate and undergraduate courses focused on computational biology and ML. Problems and methods developed through the CAREER project can be used as course material in his classes.\u003C\/p\u003E\u003Cp\u003ELuo also championed collaboration with Georgia Tech\u2019s Center for Education Integrating Science, Mathematics, and Computing (\u003Ca href=\u0022https:\/\/www.ceismc.gatech.edu\/\u0022\u003ECEISMC\u003C\/a\u003E) in his proposal.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThrough this partnership, local high school teachers and students would gain access to his data and models. This promotes deeper learning of biology and data science through hands-on experience with real-world tools. \u0026nbsp;\u003C\/p\u003E\u003Cp\u003ELuo sees reaching students and the community as a way of paying forward the support he received from Georgia Tech colleagues.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cI am incredibly grateful for this recognition from the NSF,\u201d said Luo, an assistant professor in the \u003Ca href=\u0022https:\/\/cse.gatech.edu\/\u0022\u003ESchool of Computational Science and Engineering\u003C\/a\u003E (CSE).\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThis would not have been possible without my students and collaborators, whose hard work laid the groundwork for this proposal.\u201d\u003C\/p\u003E\u003Cp\u003ELuo praised CSE faculty members \u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~badityap\/\u0022\u003EB. Aditya Prakash\u003C\/a\u003E, \u003Ca href=\u0022https:\/\/xiuweizhang.wordpress.com\/\u0022\u003EXiuwei Zhang\u003C\/a\u003E, and \u003Ca href=\u0022http:\/\/chaozhang.org\/\u0022\u003EChao Zhang\u003C\/a\u003E for their guidance. All three study \u003Ca href=\u0022https:\/\/cse.gatech.edu\/artificial-intelligence-and-machine-learning\u0022\u003Emachine learning\u003C\/a\u003E and \u003Ca href=\u0022https:\/\/cse.gatech.edu\/computational-bioscience-and-biomedicine\u0022\u003Ecomputational bioscience\u003C\/a\u003E, two of \u003Ca href=\u0022https:\/\/cse.gatech.edu\/research\u0022\u003ECSE\u2019s five core research areas\u003C\/a\u003E.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ELuo also thanked \u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~hpark\/\u0022\u003EHaesun Park\u003C\/a\u003E for her support and recommendation for the CAREER award. Park is a Regents\u2019 Professor and the chair of the School of CSE.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EProteins, including antibodies, hemoglobin, and insulin, power nearly every vital aspect of life. Breakthroughs in protein research are producing vaccines, resilient crops, bioenergy sources, and other innovative technologies.\u003C\/p\u003E\u003Cp\u003EDespite their importance, most of what scientists know about proteins only comes from a small sample size. This stands in the way of fully understanding how most proteins work and unlocking their full potential.\u003C\/p\u003E\u003Cp\u003EGeorgia Tech\u2019s \u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~yunan\/\u0022\u003EYunan Luo\u003C\/a\u003E believes artificial intelligence (AI) could fill this knowledge gap. The National Science Foundation agrees. Luo is the recipient of an NSF Faculty Early Career Development (\u003Ca href=\u0022https:\/\/www.nsf.gov\/funding\/opportunities\/career-faculty-early-career-development-program\u0022\u003ECAREER\u003C\/a\u003E) award.\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Yunan Luo is the recipient of an NSF Faculty Early Career Development (CAREER) award to use artificial intelligence to solve the protein annotation inequality problem."}],"uid":"36319","created_gmt":"2025-12-10 16:57:22","changed_gmt":"2026-01-09 13:37:31","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2025-12-10T00:00:00-05:00","iso_date":"2025-12-10T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"678817":{"id":"678817","type":"image","title":"Yunan-Luo-NSF-CAREER_1.jpg","body":null,"created":"1765385865","gmt_created":"2025-12-10 16:57:45","changed":"1765385865","gmt_changed":"2025-12-10 16:57:45","alt":"Yunan Luo NSF CAREER Award","file":{"fid":"262902","name":"Yunan-Luo-NSF-CAREER_1.jpg","image_path":"\/sites\/default\/files\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_1.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_1.jpg","mime":"image\/jpeg","size":108350,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_1.jpg?itok=j83dW4Sn"}},"678818":{"id":"678818","type":"image","title":"Yunan-Luo-NSF-CAREER_2.jpg","body":null,"created":"1765385967","gmt_created":"2025-12-10 16:59:27","changed":"1765385967","gmt_changed":"2025-12-10 16:59:27","alt":"Yunan Luo NSF CAREER Award","file":{"fid":"262903","name":"Yunan-Luo-NSF-CAREER_2.jpg","image_path":"\/sites\/default\/files\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_2.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_2.jpg","mime":"image\/jpeg","size":100260,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2025\/12\/10\/Yunan-Luo-NSF-CAREER_2.jpg?itok=CShGR6nJ"}}},"media_ids":["678817","678818"],"related_links":[{"url":"https:\/\/www.cc.gatech.edu\/news\/nsf-grant-funds-protein-research-drug-discovery-and-personalized-medicine","title":"NSF Grant Funds Protein Research for Drug Discovery and Personalized Medicine"}],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"138","name":"Biotechnology, Health, Bioengineering, Genetics"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"146","name":"Life Sciences and Biology"},{"id":"135","name":"Research"}],"keywords":[{"id":"654","name":"College of Computing"},{"id":"166983","name":"School of Computational Science and Engineering"},{"id":"9153","name":"Research Horizons"},{"id":"187915","name":"go-researchnews"},{"id":"10199","name":"Daily Digest"},{"id":"181991","name":"Georgia Tech News Center"},{"id":"9167","name":"machine learning"},{"id":"187812","name":"artificial intelligence (AI)"},{"id":"2556","name":"artificial intelligence"},{"id":"362","name":"National Science Foundation"},{"id":"191934","name":"National Science Foundation (NSF)"},{"id":"170447","name":"Institute for Data Engineering and Science"},{"id":"176858","name":"machine learning center"},{"id":"173894","name":"ML@GT"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"39441","name":"Bioengineering and Bioscience"},{"id":"39431","name":"Data Engineering and Science"}],"news_room_topics":[{"id":"71871","name":"Campus and Community"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EBryant Wine, Communications Officer\u003Cbr\u003E\u003Ca href=\u0022mailto:bryant.wine@cc.gatech.edu\u0022\u003Ebryant.wine@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}