{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:08:24Z","timestamp":1764842904789,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819751273"},{"type":"electronic","value":"9789819751280"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5128-0_32","type":"book-chapter","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T23:02:31Z","timestamp":1720738951000},"page":"395-407","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["gaBERT: An Interpretable Pretrained Deep Learning Framework for Cancer Gene Marker Discovery"],"prefix":"10.1007","author":[{"given":"Jiale","family":"Hou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zikai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinzhe","family":"Pang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunpeng","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"issue":"9","key":"32_CR1","doi-asserted-by":"publisher","first-page":"1775","DOI":"10.1200\/JCO.2003.10.108","volume":"21","author":"NH Segal","year":"2003","unstructured":"Segal, N.H., Pavlidis, P., Noble, W.S.: Classification of clear-cell sarcoma as a subtype of melanoma by genomic profiling. J. Clin. Oncol. 21(9), 1775\u20131781 (2003)","journal-title":"J. Clin. Oncol."},{"issue":"4","key":"32_CR2","doi-asserted-by":"publisher","first-page":"339","DOI":"10.30699\/ijp.2017.27990","volume":"12","author":"M Ram","year":"2017","unstructured":"Ram, M., Najafi, A., Shakeri, M.T.: Classification and biomarker genes selection for cancer gene expression data using random forest. Iran. J. Pathol. 12(4), 339 (2017)","journal-title":"Iran. J. Pathol."},{"issue":"2","key":"32_CR3","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1260\/2040-2295.4.2.255","volume":"4","author":"H Hijazi","year":"2013","unstructured":"Hijazi, H., Chan, C.: A classification framework applied to cancer gene expression profiles. J. Healthc. Eng. 4(2), 255\u2013283 (2013)","journal-title":"J. Healthc. Eng."},{"key":"32_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cmpb.2017.09.005","volume":"153","author":"Y Xiao","year":"2018","unstructured":"Xiao, Y., Wu, J., Lin, Z., Zhao, X.: A deep learning-based multi-model ensemble method for cancer prediction. Comput. Methods Programs Biomed. 153, 1\u20139 (2018)","journal-title":"Comput. Methods Programs Biomed."},{"key":"32_CR5","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Graham, S., Alemi Koohbanani, N.: CGC-Net: cell graph convolutional network for grading of colorectal cancer histology images. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 388\u2013398 (2019)","DOI":"10.1109\/ICCVW.2019.00050"},{"key":"32_CR6","unstructured":"Vaswani, A., Shazeer, N., Parmar, N.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"32_CR7","unstructured":"Devlin, J., Chang, M. W., Lee, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"issue":"10","key":"32_CR8","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1038\/s42256-022-00534-z","volume":"4","author":"F Yang","year":"2022","unstructured":"Yang, F., Wang, W., Wang, F.: ScBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data. Nat. Mach. Intell. 4(10), 852\u2013866 (2022)","journal-title":"Nat. Mach. Intell."},{"issue":"1","key":"32_CR9","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1038\/s41597-019-0207-2","volume":"6","author":"SB Lim","year":"2019","unstructured":"Lim, S.B., Tan, S.J., Lim, W.T.: Compendiums of cancer transcriptomes for machine learning applications. Sci. Data 6(1), 194 (2019)","journal-title":"Sci. Data"},{"key":"32_CR10","doi-asserted-by":"publisher","first-page":"68624","DOI":"10.3389\/fgene.2013.00290","volume":"4","author":"B Boucher","year":"2013","unstructured":"Boucher, B., Jenna, S.: Genetic interaction networks: better understand to better predict. Front. Genet. 4, 68624 (2013)","journal-title":"Front. Genet."},{"issue":"1","key":"32_CR11","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1038\/s41598-017-18705-z","volume":"8","author":"J Li","year":"2018","unstructured":"Li, J., Zhou, D., Qiu, W.: Application of weighted gene co-expression network analysis for data from paired design. Sci. Rep. 8(1), 622 (2018)","journal-title":"Sci. Rep."},{"key":"32_CR12","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2018.00682","volume":"9","author":"CT Choy","year":"2019","unstructured":"Choy, C.T., Wong, C.H.: Embedding of genes using cancer gene expression data: biological relevance and potential application on biomarker discovery. Front. Genet. 9, 421857 (2019)","journal-title":"Front. Genet."},{"key":"32_CR13","unstructured":"Mikolov, T., Chen, K., Corrado, G.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)"},{"key":"32_CR14","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s12864-018-5370-x","volume":"20","author":"J Du","year":"2019","unstructured":"Du, J., Jia, P., Dai, Y.: Gene2vec: distributed representation of genes based on co-expression. BMC Genomics 20, 7\u201315 (2019)","journal-title":"BMC Genomics"},{"issue":"43","key":"32_CR15","doi-asserted-by":"publisher","first-page":"15545","DOI":"10.1073\/pnas.0506580102","volume":"102","author":"A Subramanian","year":"2005","unstructured":"Subramanian, A., Tamayo, P., Mootha, V.K.: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. 102(43), 15545\u201315550 (2005)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"32_CR16","unstructured":"Choromanski, K., Likhosherstov, V., Dohan, D.: Rethinking attention with performers. arXiv preprint arXiv:2009.14794 (2020)"},{"key":"32_CR17","doi-asserted-by":"crossref","unstructured":"Montavon, G., Binder, A., Lapuschkin, S.: Layer-wise relevance propagation: an overview. Explainable AI: interpreting, explaining and visualizing deep learning, 193\u2013209 (2019)","DOI":"10.1007\/978-3-030-28954-6_10"},{"key":"32_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/gb-2003-4-9-r60","volume":"4","author":"G Dennis","year":"2003","unstructured":"Dennis, G., Sherman, B.T., Hosack, D.A.: DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 4, 1\u201311 (2003)","journal-title":"Genome Biol."},{"issue":"1","key":"32_CR19","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","volume":"28","author":"M Kanehisa","year":"2000","unstructured":"Kanehisa, M., Goto, S.: KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28(1), 27\u201330 (2000)","journal-title":"Nucleic Acids Res."},{"issue":"12","key":"32_CR20","doi-asserted-by":"publisher","first-page":"1887","DOI":"10.1097\/JTO.0b013e3181f77a53","volume":"5","author":"MO Hoque","year":"2010","unstructured":"Hoque, M.O., Brait, M., Rosenbaum, E.: Genetic and epigenetic analysis of erbB signaling pathway genes in lung cancer. J. Thorac. Oncol. 5(12), 1887\u20131893 (2010)","journal-title":"J. Thorac. Oncol."},{"issue":"4","key":"32_CR21","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1159\/000229775","volume":"80","author":"M Yonezawa","year":"2009","unstructured":"Yonezawa, M., Wada, K., Tatsuguchi, A.: Heregulin-induced VEGF expression via the ErbB3 signaling pathway in colon cancer. Digestion 80(4), 215\u2013225 (2009)","journal-title":"Digestion"},{"issue":"2","key":"32_CR22","doi-asserted-by":"publisher","first-page":"595","DOI":"10.3892\/ijo.2015.3270","volume":"48","author":"M Wang","year":"2016","unstructured":"Wang, M., Ren, D., Guo, W.: N-cadherin promotes epithelial-mesenchymal transition and cancer stem cell-like traits via ErbB signaling in prostate cancer cells. Int. J. Oncol. 48(2), 595\u2013606 (2016)","journal-title":"Int. J. Oncol."},{"issue":"7","key":"32_CR23","doi-asserted-by":"publisher","first-page":"11719","DOI":"10.18632\/oncotarget.14319","volume":"8","author":"T Liao","year":"2017","unstructured":"Liao, T., Wen, D., Ma, B.: Yes-associated protein 1 promotes papillary thyroid cancer cell proliferation by activating the ERK\/MAPK signaling pathway. Oncotarget 8(7), 11719 (2017)","journal-title":"Oncotarget"},{"issue":"1","key":"32_CR24","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1517\/14728222.2011.641951","volume":"16","author":"MJ Waldner","year":"2012","unstructured":"Waldner, M.J., Neurath, M.F.: Targeting the VEGF signaling pathway in cancer therapy. Expert Opin. Ther. Targets 16(1), 5\u201313 (2012)","journal-title":"Expert Opin. Ther. Targets"},{"issue":"1","key":"32_CR25","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1111\/cas.13429","volume":"109","author":"F Liu","year":"2018","unstructured":"Liu, F., Bu, Z., Zhao, F.: Increased T-helper 17 cell differentiation mediated by exosome-mediated micro RNA-451 redistribution in gastric cancer infiltrated T cells. Cancer Sci. 109(1), 65\u201373 (2018)","journal-title":"Cancer Sci."},{"issue":"7991","key":"32_CR26","first-page":"890","volume":"2","author":"M Chen","year":"2011","unstructured":"Chen, M.: Platinum resistance in ovarian cancer: a molecular analysis of the p13k\/akt pathway. Imperial College London 2(7991), 890\u2013891 (2011)","journal-title":"Imperial College London"}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5128-0_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T18:05:01Z","timestamp":1731953101000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5128-0_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819751273","9789819751280"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5128-0_32","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"12 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISBRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Bioinformatics Research and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kunming","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/bio.csu.edu.cn\/ISBRA2024\/ISBRA2024_Home.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}