{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T22:42:06Z","timestamp":1785796926082,"version":"3.56.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T00:00:00Z","timestamp":1728864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T00:00:00Z","timestamp":1728864000000},"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":["Endocrine"],"DOI":"10.1007\/s12020-024-04068-9","type":"journal-article","created":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T14:02:52Z","timestamp":1728914572000},"page":"758-771","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Identification of potential biomarkers of papillary thyroid carcinoma"],"prefix":"10.1007","volume":"87","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9299-7141","authenticated-orcid":false,"given":"Sabire","family":"Kilicarslan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4303-9717","authenticated-orcid":false,"given":"Meliha Merve","family":"Hiz-Cicekliyurt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,10,14]]},"reference":[{"key":"4068_CR1","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3322\/caac.21820","volume":"74","author":"RL Siegel","year":"2024","unstructured":"R.L. Siegel, A.N. Giaquinto, A. Jemal, Cancer statistics, 2024. CA. Cancer J. Clin. 74, 12\u201349 (2024).","journal-title":"CA. Cancer J. Clin."},{"key":"4068_CR2","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.otc.2023.08.007","volume":"57","author":"B Scott","year":"2023","unstructured":"B. Scott, R.J. Wong, Step-by-Step Thyroidectomy-Incision, check for updates nerve identification, parathyroid preservation, and gland removal. Otolaryngol. Clin. N. Am. E-Book 57, 25 (2023).","journal-title":"Otolaryngol. Clin. N. Am. E-Book"},{"key":"4068_CR3","doi-asserted-by":"publisher","first-page":"e208759","DOI":"10.1001\/jamanetworkopen.2020.8759","volume":"3","author":"Y Deng","year":"2020","unstructured":"Y. Deng et al. Global burden of thyroid cancer from 1990 to 2017. JAMA Netw. Open 3, e208759\u2013e208759 (2020).","journal-title":"JAMA Netw. Open"},{"key":"4068_CR4","doi-asserted-by":"publisher","first-page":"63","DOI":"10.4158\/EP.12.1.63","volume":"12","author":"H Gharib","year":"2006","unstructured":"H. Gharib et al. American Association of Clinical Endocrinologists and Associazione Medici Endocrinologi Medical Guidelines for Clinical Practice for the Diagnosis and Management of thyroid nodules. Endocr. Pract. 12, 63\u2013102 (2006).","journal-title":"Endocr. Pract."},{"key":"4068_CR5","doi-asserted-by":"publisher","first-page":"383","DOI":"10.3390\/cancers12020383","volume":"12","author":"L Fugazzola","year":"2020","unstructured":"L. Fugazzola, M. Muzza, G. Pogliaghi, M. Vitale, Intratumoral genetic heterogeneity in papillary thyroid cancer: occurrence and clinical significance. Cancers 12, 383 (2020).","journal-title":"Cancers"},{"key":"4068_CR6","doi-asserted-by":"publisher","first-page":"2111","DOI":"10.1007\/s11010-022-04606-x","volume":"478","author":"M Liao","year":"2023","unstructured":"M. Liao, Z. Wang, J. Yao, H. Xing, Y. Hao, B. Qiu, Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis. Mol. Cell. Biochem. 478, 2111\u20132123 (2023).","journal-title":"Mol. Cell. Biochem."},{"key":"4068_CR7","doi-asserted-by":"publisher","first-page":"1250","DOI":"10.3390\/genes14061250","volume":"14","author":"I Petrini","year":"2023","unstructured":"I. Petrini, R.L. Cecchini, M. Mascar\u00f3, I. Ponzoni, J.A. Carballido, Papillary thyroid carcinoma: a thorough bioinformatic analysis of gene expression and clinical data. Genes 14, 1250 (2023).","journal-title":"Genes"},{"key":"4068_CR8","doi-asserted-by":"publisher","first-page":"624421","DOI":"10.3389\/fonc.2021.624421","volume":"11","author":"H Ren","year":"2021","unstructured":"H. Ren, X. Liu, F. Li, X. He, N. Zhao, Identification of a six gene prognosis signature for papillary thyroid cancer using multi-omics methods and bioinformatics analysis. Front. Oncol. 11, 624421 (2021).","journal-title":"Front. Oncol."},{"key":"4068_CR9","doi-asserted-by":"publisher","first-page":"45","DOI":"10.3390\/genes10010045","volume":"10","author":"J Shang","year":"2019","unstructured":"J. Shang, Q. Ding, S. Yuan, J.-X. Liu, F. Li, H. Zhang, Network analyses of integrated differentially expressed genes in papillary thyroid carcinoma to identify characteristic genes. Genes 10, 45 (2019).","journal-title":"Genes"},{"key":"4068_CR10","doi-asserted-by":"publisher","unstructured":"S. Li, Y. Yin, H. Yu, Genetic expression profile\u2011based screening of genes and pathways associated with papillary thyroid carcinoma. Oncol. Lett. (2018). https:\/\/doi.org\/10.3892\/ol.2018.9342","DOI":"10.3892\/ol.2018.9342"},{"key":"4068_CR11","doi-asserted-by":"publisher","first-page":"2803","DOI":"10.1073\/pnas.0610733104","volume":"104","author":"V Vasko","year":"2007","unstructured":"V. Vasko et al. Gene expression and functional evidence of epithelial-to-mesenchymal transition in papillary thyroid carcinoma invasion. Proc. Natl. Acad. Sci. 104, 2803\u20132808 (2007). https:\/\/doi.org\/10.1073\/pnas.0610733104","journal-title":"Proc. Natl. Acad. Sci."},{"key":"4068_CR12","doi-asserted-by":"publisher","first-page":"19075","DOI":"10.1073\/pnas.0509603102","volume":"102","author":"H He","year":"2005","unstructured":"H. He et al. The role of microRNA genes in papillary thyroid carcinoma. Proc. Natl. Acad. Sci. 102, 19075\u201319080 (2005). https:\/\/doi.org\/10.1073\/pnas.0509603102","journal-title":"Proc. Natl. Acad. Sci."},{"key":"4068_CR13","doi-asserted-by":"publisher","first-page":"4490","DOI":"10.1038\/onc.2011.626","volume":"31","author":"G Tom\u00e1s","year":"2012","unstructured":"G. Tom\u00e1s et al. A general method to derive robust organ-specific gene expression-based differentiation indices: application to thyroid cancer diagnostic. Oncogene 31, 4490\u20134498 (2012).","journal-title":"Oncogene"},{"key":"4068_CR14","unstructured":"D. Anguita, L. Ghelardoni, A. Ghio, L. Oneto, S. Ridella, \u201cThe\u2019K\u2019in K-fold Cross Validation.,\u201d in ESANN, 2012, pp. 441\u2013446. Accessed: Aug. 25, 2024. [Online]."},{"key":"4068_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2202\/1544-6115.1027","volume":"3","author":"GK Smyth","year":"2004","unstructured":"G.K. Smyth, Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, 1\u201325 (2004). https:\/\/doi.org\/10.2202\/1544-6115.1027","journal-title":"Stat. Appl. Genet. Mol. Biol."},{"key":"4068_CR16","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/S0166-4328(01)00297-2","volume":"125","author":"Y Benjamini","year":"2001","unstructured":"Y. Benjamini, D. Drai, G. Elmer, N. Kafkafi, I. Golani, Controlling the false discovery rate in behavior genetics research. Behav. Brain Res. 125, 279\u2013284 (2001).","journal-title":"Behav. Brain Res."},{"key":"4068_CR17","doi-asserted-by":"publisher","DOI":"10.1186\/1752-0509-7-S4-S1","volume":"7","author":"Y Bei","year":"2013","unstructured":"Y. Bei, P. Hong, A novel approach to minimize false discovery rate in genome-wide data analysis. BMC Syst. Biol. 7, S1 (2013). https:\/\/doi.org\/10.1186\/1752-0509-7-S4-S1","journal-title":"BMC Syst. Biol."},{"key":"4068_CR18","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1093\/bioinformatics\/btf877","volume":"19","author":"A Reiner","year":"2003","unstructured":"A. Reiner, D. Yekutieli, Y. Benjamini, Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics 19, 368\u2013375 (2003).","journal-title":"Bioinformatics"},{"key":"4068_CR19","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1093\/bib\/1.4.398","volume":"1","author":"R Stevens","year":"2000","unstructured":"R. Stevens, C.A. Goble, S. Bechhofer, Ontology-based knowledge representation for bioinformatics. Brief. Bioinform. 1, 398\u2013414 (2000).","journal-title":"Brief. Bioinform."},{"key":"4068_CR20","doi-asserted-by":"publisher","first-page":"D480","DOI":"10.1093\/nar\/gkm882","volume":"36","author":"M Kanehisa","year":"2007","unstructured":"M. Kanehisa et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36, D480\u2013D484 (2007).","journal-title":"Nucleic Acids Res"},{"key":"4068_CR21","doi-asserted-by":"publisher","unstructured":"H. Wickham, ggplot2. in Use R! Cham: Springer International Publishing, (2016). https:\/\/doi.org\/10.1007\/978-3-319-24277-4","DOI":"10.1007\/978-3-319-24277-4"},{"key":"4068_CR22","doi-asserted-by":"crossref","unstructured":"C.-H. Gao, G. Yu, and P. Cai, ggVennDiagram: an intuitive, easy-to-use, and highly customizable R package to generate Venn diagram. Front. Genet., 1598 (2021).","DOI":"10.3389\/fgene.2021.706907"},{"key":"4068_CR23","doi-asserted-by":"publisher","first-page":"1478","DOI":"10.1002\/pmic.201100563","volume":"12","author":"P Braun","year":"2012","unstructured":"P. Braun, A. Gingras, History of protein\u2013protein interactions: From egg\u2010white to complex networks. PROTEOMICS 12, 1478\u20131498 (2012). https:\/\/doi.org\/10.1002\/pmic.201100563","journal-title":"PROTEOMICS"},{"key":"4068_CR24","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"L. Breiman, Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"4068_CR25","doi-asserted-by":"crossref","unstructured":"T. Mahboob, S. Irfan, A. Karamat, \u201cA machine learning approach for student assessment in E-learning using Quinlan\u2019s C4. 5, Naive Bayes and Random Forest algorithms,\u201d in 2016 19th International Multi-topic Conference (INMIC), IEEE, 2016, pp. 1\u20138. Accessed: Feb. 05, 2024.","DOI":"10.1109\/INMIC.2016.7840094"},{"key":"4068_CR26","unstructured":"S.G. Eraldemir, M.T. Arslan, Y. Esen, \u201cComparison of random forest and J48 decision tree classifiers using HHT based features in EEG,\u201d in International Advanced Researches & Engineering Congress-2017, 2017. Accessed: Feb. 05, 2024."},{"key":"4068_CR27","doi-asserted-by":"publisher","first-page":"769","DOI":"10.29130\/dubited.464092","volume":"7","author":"S Kilicarslan","year":"2019","unstructured":"S. Kilicarslan, A. Kemal, O. C\u00f6mert, Par\u00e7ac\u0131k s\u00fcr\u00fc optimizasyonu kullan\u0131larak boyutu azalt\u0131lm\u0131\u015f mikrodizi verileri \u00fczerinde makine \u00f6\u011frenmesi y\u00f6ntemleri ile prostat kanseri te\u015fhisi. D\u00fczce \u00dcniversitesi Bilim Ve Teknol. Derg. 7, 769\u2013777 (2019).","journal-title":"D\u00fczce \u00dcniversitesi Bilim Ve Teknol. Derg."},{"key":"4068_CR28","doi-asserted-by":"publisher","first-page":"102231","DOI":"10.1016\/j.bspc.2020.102231","volume":"63","author":"S Kilicarslan","year":"2021","unstructured":"S. Kilicarslan, M. Celik, \u015e. Sahin, \u201cHybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification,\u201d. Biomed. Signal Process. Control 63, 102231 (2021).","journal-title":"Biomed. Signal Process. Control"},{"key":"4068_CR29","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1109\/PGEC.1965.264137","volume":"3","author":"TM Cover","year":"1965","unstructured":"T.M. Cover, Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition. IEEE Trans. Electron. Comput. 3, 326\u2013334 (1965).","journal-title":"IEEE Trans. Electron. Comput."},{"key":"4068_CR30","unstructured":"V. Vapnik, The nature of statistical learning theory. Springer science & business media, 1999. Accessed: Feb. 05, 2024."},{"key":"4068_CR31","doi-asserted-by":"publisher","unstructured":"S. Kili\u00e7arslan and E. D\u00f6nmez, Improved multi-layer hybrid adaptive particle swarm optimization based artificial bee colony for optimizing feature selection and classification of microarray data. Multimed. Tools Appl. (2023), https:\/\/doi.org\/10.1007\/s11042-023-17234-4","DOI":"10.1007\/s11042-023-17234-4"},{"key":"4068_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3136625","volume":"50","author":"J Li","year":"2018","unstructured":"J. Li et al. Feature selection: a data perspective. ACM Comput. Surv. 50, 1\u201345 (2018). https:\/\/doi.org\/10.1145\/3136625","journal-title":"ACM Comput. Surv."},{"key":"4068_CR33","doi-asserted-by":"crossref","unstructured":"F. Arag\u00f3n-Roy\u00f3n, A. Jim\u00e9nez-V\u00edlchez, A. Arauzo-Azofra, J.M. Ben\u00edtez, FSinR: an exhaustive package for feature selection. (2020). arXiv: arXiv:2002.10330.","DOI":"10.32614\/CRAN.package.FSinR"},{"key":"4068_CR34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","volume":"28","author":"M Kuhn","year":"2008","unstructured":"M. Kuhn, Caret package. J. Stat. Softw. 28, 1\u201326 (2008).","journal-title":"J. Stat. Softw."},{"key":"4068_CR35","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1007\/s00500-008-0392-y","volume":"13","author":"S Garc\u00eda","year":"2009","unstructured":"S. Garc\u00eda, A. Fern\u00e1ndez, J. Luengo, F. Herrera, A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability. Soft Comput. 13, 959\u2013977 (2009).","journal-title":"Soft Comput"},{"key":"4068_CR36","first-page":"197","volume":"6","author":"M Doshi","year":"2014","unstructured":"M. Doshi, Correlation based feature selection (CFS) technique to predict student performance. Int. J. Comput. Netw. Commun. 6, 197 (2014).","journal-title":"Int. J. Comput. Netw. Commun."},{"key":"4068_CR37","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.jbi.2018.07.014","volume":"85","author":"RJ Urbanowicz","year":"2018","unstructured":"R.J. Urbanowicz, M. Meeker, W. La Cava, R.S. Olson, J.H. Moore, Relief-based feature selection: Introduction and review. J. Biomed. Inform. 85, 189\u2013203 (2018).","journal-title":"J. Biomed. Inform."},{"key":"4068_CR38","doi-asserted-by":"publisher","first-page":"117693","DOI":"10.1016\/j.lfs.2020.117693","volume":"253","author":"D Meng","year":"2020","unstructured":"D. Meng, Z. Li, X. Ma, L. Wu, L. Fu, G. Qin, ETV5 overexpression contributes to tumor growth and progression of thyroid cancer through PIK3CA. Life Sci. 253, 117693 (2020).","journal-title":"Life Sci"},{"key":"4068_CR39","doi-asserted-by":"publisher","first-page":"e55971","DOI":"10.1371\/journal.pone.0055971","volume":"8","author":"SM Gaikwad","year":"2013","unstructured":"S.M. Gaikwad, L. Gunjal, A.R. Junutula, A. Astanehe, S.S. Gambhir, P. Ray, Non-invasive imaging of phosphoinositide-3-kinase-catalytic-subunit-alpha (PIK3CA) promoter modulation in small animal models. PLoS One 8, e55971 (2013).","journal-title":"PLoS One"},{"key":"4068_CR40","doi-asserted-by":"publisher","first-page":"8131","DOI":"10.18632\/oncotarget.14101","volume":"8","author":"C Da","year":"2017","unstructured":"C. Da et al. N-cadherin promotes thyroid tumorigenesis through modulating major signaling pathways. Oncotarget 8, 8131 (2017).","journal-title":"Oncotarget"},{"key":"4068_CR41","doi-asserted-by":"publisher","first-page":"4430","DOI":"10.7150\/jca.24361","volume":"9","author":"X Lin","year":"2018","unstructured":"X. Lin et al. TFF3 contributes to epithelial-mesenchymal transition (EMT) in papillary thyroid carcinoma cells via the MAPK\/ERK signaling pathway. J. Cancer 9, 4430 (2018).","journal-title":"J. Cancer"},{"key":"4068_CR42","doi-asserted-by":"publisher","first-page":"154431","DOI":"10.1016\/j.prp.2023.154431","volume":"245","author":"T Liang","year":"2023","unstructured":"T. Liang et al. Clinical significance and diagnostic value of QPCT, SCEL and TNFRSF12A in papillary thyroid cancer. Pathol.-Res. Pract. 245, 154431 (2023).","journal-title":"Pathol.-Res. Pract."},{"key":"4068_CR43","doi-asserted-by":"publisher","first-page":"5043","DOI":"10.1200\/JCO.2006.06.7330","volume":"24","author":"OL Griffith","year":"2006","unstructured":"O.L. Griffith, A. Melck, S.J. Jones, S.M. Wiseman, Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers. J. Clin. Oncol. 24, 5043\u20135051 (2006).","journal-title":"J. Clin. Oncol."},{"key":"4068_CR44","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1530\/ERC-12-0053","volume":"20","author":"A Kehlen","year":"2013","unstructured":"A. Kehlen et al. Role of glutaminyl cyclases in thyroid carcinomas. Endocr. Relat. Cancer 20, 79\u201390 (2013).","journal-title":"Endocr. Relat. Cancer"},{"key":"4068_CR45","first-page":"245","volume":"31","author":"E. G\u00f6v","year":"2019","unstructured":"E. G\u00f6v, \u201cIdentification of thyroid carcinoma related molecular targets and signatures using human protein interaction network. Int. J. Adv. Eng. Pure Sci. 31, 245\u2013254 (2019).","journal-title":"Int. J. Adv. Eng. Pure Sci."},{"key":"4068_CR46","doi-asserted-by":"publisher","first-page":"962","DOI":"10.3892\/or.2015.4466","volume":"35","author":"L Chai","year":"2016","unstructured":"L. Chai, J. Li, Z. Lv, An integrated analysis of cancer genes in thyroid cancer. Oncol. Rep. 35, 962\u2013970 (2016).","journal-title":"Oncol. Rep."},{"key":"4068_CR47","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.bbrc.2018.06.012","volume":"503","author":"X Zhou","year":"2018","unstructured":"X. Zhou et al. LRP4 promotes proliferation, migration, and invasion in papillary thyroid cancer. Biochem. Biophys. Res. Commun. 503, 257\u2013263 (2018).","journal-title":"Biochem. Biophys. Res. Commun."},{"key":"4068_CR48","doi-asserted-by":"publisher","first-page":"776","DOI":"10.1038\/s41416-019-0589-0","volume":"121","author":"C Joseph","year":"2019","unstructured":"C. Joseph et al. Retinoid X receptor gamma (RXRG) is an independent prognostic biomarker in ER-positive invasive breast cancer. Br. J. Cancer 121, 776\u2013785 (2019).","journal-title":"Br. J. Cancer"}],"container-title":["Endocrine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12020-024-04068-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12020-024-04068-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12020-024-04068-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T12:30:14Z","timestamp":1739190614000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12020-024-04068-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,14]]},"references-count":48,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["4068"],"URL":"https:\/\/doi.org\/10.1007\/s12020-024-04068-9","relation":{},"ISSN":["1559-0100"],"issn-type":[{"value":"1559-0100","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,14]]},"assertion":[{"value":"4 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}