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In this paper, we systematically test this assumption on 3 protein benchmark datasets with 2 convolutional neural networks and show that different vertex assignments lead to significant differences in classification performance. Evaluating 1,000 random encodings revealed a wide performance range, proving that vertex assignment is a critical parameter rather than an arbitrary choice. Furthermore, in most of the cases, frequency chaos game representation-based data augmentation proved to be effective only under moderate settings, while aggressive augmentation degraded performance due to distributional shifts introduced by permuted encodings.<\/jats:p>","DOI":"10.34133\/csbj.0225","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:14:36Z","timestamp":1788135276000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["Vertex Assignment for Frequency Chaos Game Representation of Proteins Affects Classification Performance"],"prefix":"10.34133","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4743-3259","authenticated-orcid":true,"given":"B\u00e1lint","family":"Bir\u00f3","sequence":"first","affiliation":[{"name":"Group BM, Data Insights Team, _VOIS","place":["Hungary"]},{"name":"Department of Animal Biotechnology, Institute of Genetics and Biotechnology, \rHungarian University of Agriculture and Life Sciences, G\u00f6d\u00f6ll\u0151, Hungary."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T\u00edmea","family":"Subicz","sequence":"additional","affiliation":[{"name":"Group BM, Data Insights Team, _VOIS","place":["Hungary"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00f3bert","family":"Barta","sequence":"additional","affiliation":[{"name":"Department of Animal Biotechnology, Institute of Genetics and Biotechnology, \rHungarian University of Agriculture and Life Sciences, G\u00f6d\u00f6ll\u0151, Hungary."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soma S\u00e1ndor","family":"Hartai","sequence":"additional","affiliation":[{"name":"Department of Animal Biotechnology, Institute of Genetics and Biotechnology, \rHungarian University of Agriculture and Life Sciences, G\u00f6d\u00f6ll\u0151, Hungary."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1023-0112","authenticated-orcid":false,"given":"L\u00e1szl\u00f3","family":"Hiripi","sequence":"additional","affiliation":[{"name":"Department of Animal Biotechnology, Institute of Genetics and Biotechnology, \rHungarian University of Agriculture and Life Sciences, G\u00f6d\u00f6ll\u0151, Hungary."},{"name":"Laboratory Animal Science Coordination Center, \rSemmelweis University, Budapest, Hungary."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Orsolya Ivett","family":"Hoffmann","sequence":"additional","affiliation":[{"name":"Department of Animal Biotechnology, Institute of Genetics and Biotechnology, \rHungarian University of Agriculture and Life Sciences, G\u00f6d\u00f6ll\u0151, Hungary."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2026,9,14]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.4c00546"},{"issue":"1","key":"e_1_3_2_3_2","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1186\/s13321-026-01183-9","article-title":"Contrastive representation learning and capsule networks enable accurate identification of ferroptosis-related proteins","volume":"18","author":"Zhao Y","year":"2026","unstructured":"Zhao Y, Liu X, Xie P, Guan J, Zhao Z, Wang J, Lee TY, Chiang YC, Wei L, Liu X, et al. 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