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A key research focus within this field is spatial domain identification, which is essential for exploring tissue organization, biological development, and disease mechanisms. Although methods have been developed, they still face challenges in modeling GE\u00a0information together with spatial locations, resulting in suboptimal accuracy. Here, we introduce Distribution-aware Contrastive Learning for Spatial Transcriptomics (DisConST), a novel deep learning method designed to improve spatial domain detection within ST datasets. DisConST addresses key challenges, such as the high dropout rates and the complex integration of spatial and GE data, by incorporating contrastive learning strategies that are aware of the underlying data distributions. It employs the zero-inflated negative binomial distribution, along with graph contrastive learning, to generate more informative latent representations. These representations efficiently integrate spatial positions, transcriptomic profiles, and cell-type proportions within spots. We validated DisConST across diverse ST datasets of tissues, organs, and embryos from various sequencing platforms in both normal and disease states. Our results consistently demonstrate that DisConST achieves superior spatial domain recognition accuracy compared to existing state-of-the-art methods. Furthermore, our experiments highlight the utility of DisConST in advancing research on tissue organization, embryonic development, and tumor immune microenvironment dissection. The source code for DisConST is freely available at https:\/\/github.com\/Zhenpm\/DisConST\/.<\/jats:p>","DOI":"10.1093\/gpbjnl\/qzaf085","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T14:05:41Z","timestamp":1758722741000},"source":"Crossref","is-referenced-by-count":7,"title":["DisConST: Distribution-aware Contrastive Learning for Spatial Domain Identification"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5504-6321","authenticated-orcid":false,"given":"Peimeng","family":"Zhen","sequence":"first","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9157-2898","authenticated-orcid":false,"given":"Xiaofeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of General Surgery, The Affiliated Hospital of Northwest University, Xi\u2019an No. 3 Hospital, Xi\u2019an 710018,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5854-0526","authenticated-orcid":false,"given":"Han","family":"Shu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3351-8020","authenticated-orcid":false,"given":"Jialu","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2766-3106","authenticated-orcid":false,"given":"Yongtian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3857-7927","authenticated-orcid":false,"given":"Jiajie","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7249-8210","authenticated-orcid":false,"given":"Xuequn","family":"Shang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an 710072,","place":["China"]},{"name":"Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern 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