{"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/high-quality-prediction-of-protein-q8","title":"High Quality Prediction of Protein Q8 Secondary Structure by Diverse Neural Network Architectures","arxiv_id":"1811.07143","date":"2018-11-17","proceeding":null,"authors":["Iddo Drori","Isht Dwivedi","Pranav Shrestha","Jeffrey Wan","Yueqi Wang","Yunchu He","Anthony Mazza","Hugh Krogh-Freeman","Dimitri Leggas","Kendal Sandridge","Linyong Nan","Kaveri Thakoor","Chinmay Joshi","Sonam Goenka","Chen Keasar","Itsik Pe'er"],"abstract":"We tackle the problem of protein secondary structure prediction using a\ncommon task framework. This lead to the introduction of multiple ideas for\nneural architectures based on state of the art building blocks, used in this\ntask for the first time. We take a principled machine learning approach, which\nprovides genuine, unbiased performance measures, correcting longstanding errors\nin the application domain. We focus on the Q8 resolution of secondary\nstructure, an active area for continuously improving methods. We use an\nensemble of strong predictors to achieve accuracy of 70.7% (on the CB513 test\nset using the CB6133filtered training set). These results are statistically\nindistinguishable from those of the top existing predictors. In the spirit of\nreproducible research we make our data, models and code available, aiming to\nset a gold standard for purity of training and testing sets. Such good\npractices lower entry barriers to this domain and facilitate reproducible,\nextendable research.","url_abs":"http://arxiv.org/abs/1811.07143v1","url_pdf":"http://arxiv.org/pdf/1811.07143v1.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":"high-quality-prediction-of-protein-q8","repo_url":"https://github.com/idrori/cu-ssp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"high-quality-prediction-of-protein-q8","repo_url":"https://github.com/siditom-cs/meshi_ssp_light","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"protein-secondary-structure-prediction","task_name":"Protein Secondary Structure 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}