{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T21:05:19Z","timestamp":1757624719806,"version":"3.44.0"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032014351"},{"type":"electronic","value":"9783032014368"}],"license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-01436-8_14","type":"book-chapter","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T03:25:24Z","timestamp":1755487524000},"page":"258-275","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding Gene Regulation in\u00a0Alzheimer\u2019s Disease with\u00a0Transfer Learning and\u00a0Explainable Machine Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9004-3033","authenticated-orcid":false,"given":"Sergio","family":"Peignier","sequence":"first","affiliation":[]},{"given":"Amanda","family":"Lo Van","sequence":"additional","affiliation":[]},{"given":"Yann","family":"Meunier","sequence":"additional","affiliation":[]},{"given":"Elea","family":"Pauliat","sequence":"additional","affiliation":[]},{"given":"Matis","family":"Zouari","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7856-9617","authenticated-orcid":false,"given":"Federica","family":"Calevro","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Aibar, S., Gonz\u00e1lez-Blas, C.B., Moerman, et\u00a0al.: Scenic: single-cell regulatory network inference and clustering. Nat. Methods 14(11), 1083\u20131086 (2017)","key":"14_CR1","DOI":"10.1038\/nmeth.4463"},{"doi-asserted-by":"crossref","unstructured":"Ali, M., Huarte, O.U., Heurtaux, T., et\u00a0al.: Single-cell transcriptional profiling and gene regulatory network modeling in TG2576 mice reveal gender-dependent molecular features preceding Alzheimer-like pathologies. Mol. Neurobiol. 61(2), 541\u2013566 (2024)","key":"14_CR2","DOI":"10.1007\/s12035-022-02985-2"},{"issue":"11","key":"14_CR3","doi-asserted-by":"publisher","first-page":"3249","DOI":"10.1109\/TMI.2021.3077857","volume":"40","author":"S Bhadra","year":"2021","unstructured":"Bhadra, S., Kelkar, V.A., Brooks, F.J., Anastasio, M.A.: On hallucinations in tomographic image reconstruction. IEEE Trans. Med. Imaging 40(11), 3249\u20133260 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"unstructured":"Buitinck, L., Louppe, G., Blondel, M., Pedregosa, F., et\u00a0al.: API design for machine learning software: experiences from the scikit-learn project. In: ECML PKDD Workshop: Languages for Data Mining and Machine Learning, pp. 108\u2013122 (2013)","key":"14_CR4"},{"issue":"9","key":"14_CR5","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/j.disamonth.2010.06.001","volume":"56","author":"RJ Castellani","year":"2010","unstructured":"Castellani, R.J., Rolston, R.K., Smith, M.A.: Alzheimer disease. Disease-a-month: DM 56(9), 484 (2010)","journal-title":"Disease-a-month: DM"},{"issue":"1","key":"14_CR6","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1017\/S1461145711000149","volume":"15","author":"CH Chen","year":"2012","unstructured":"Chen, C.H., Zhou, W., Liu, S., Deng, Y., et al.: Increased NF-$$\\kappa $$B signalling up-regulates BACE1 expression and its therapeutic potential in Alzheimer\u2019s disease. Int. J. Neuropsychopharmacol. 15(1), 77\u201390 (2012)","journal-title":"Int. J. Neuropsychopharmacol."},{"issue":"6","key":"14_CR7","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.70.066111","volume":"70","author":"A Clauset","year":"2004","unstructured":"Clauset, A., Newman, M.E., Moore, C.: Finding community structure in very large networks. Phys. Rev. E 70(6), 066111 (2004)","journal-title":"Phys. Rev. E"},{"issue":"4","key":"14_CR8","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1161\/CIRCRESAHA.118.313316","volume":"124","author":"M Corada","year":"2019","unstructured":"Corada, M., Orsenigo, F., Bhat, G.P., et al.: Fine-tuning of Sox17 and canonical WNT coordinates the permeability properties of the blood-brain barrier. Circ. Res. 124(4), 511\u2013525 (2019)","journal-title":"Circ. Res."},{"doi-asserted-by":"crossref","unstructured":"Cui, H., et al.: scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat. Methods, 1\u201311 (2024)","key":"14_CR9","DOI":"10.1101\/2023.04.30.538439"},{"doi-asserted-by":"crossref","unstructured":"Feng, G., Qin, X., Zhang, J., Huang, W., et\u00a0al.: CellPolaris: decoding cell fate through generalization transfer learning of gene regulatory networks. bioRxiv, 2023\u201309 (2023)","key":"14_CR10","DOI":"10.1101\/2023.09.25.559244"},{"doi-asserted-by":"publisher","unstructured":"Hokama, M., Oka, S., Leon, J., et\u00a0al.: Altered expression of diabetes-related genes in Alzheimer\u2019s disease brains: the Hisayama study. Cereb. Cortex (New York, N.Y. 1991) 24(9), 2476\u20132488 (2014). https:\/\/doi.org\/10.1093\/cercor\/bht101","key":"14_CR11","DOI":"10.1093\/cercor\/bht101"},{"doi-asserted-by":"crossref","unstructured":"Huynh-Thu, V.A., Sanguinetti, G.: Gene regulatory network inference: an introductory survey. Gene Regul. Netw. Methods Protoc., 1\u201323 (2019)","key":"14_CR12","DOI":"10.1007\/978-1-4939-8882-2_1"},{"key":"14_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/alzrt155","volume":"5","author":"WA Jefferies","year":"2013","unstructured":"Jefferies, W.A., Price, K.A., Biron, K.E., Fenninger, F., Pfeifer, C.G., Dickstein, D.L.: Adjusting the compass: new insights into the role of angiogenesis in Alzheimer\u2019s disease. Alzheimer\u2019s Res. Therapy 5, 1\u20139 (2013)","journal-title":"Alzheimer\u2019s Res. Therapy"},{"issue":"12","key":"14_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3571730","volume":"55","author":"Z Ji","year":"2023","unstructured":"Ji, Z., et al.: Survey of hallucination in natural language generation. ACM Comput. Surv. 55(12), 1\u201338 (2023)","journal-title":"ACM Comput. Surv."},{"issue":"11","key":"14_CR15","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1093\/hmg\/ddad009","volume":"32","author":"S Khullar","year":"2023","unstructured":"Khullar, S., Wang, D.: Predicting brain-regional gene regulatory networks from multi-omics for Alzheimer\u2019s disease phenotypes and covid-19 severity. Hum. Mol. Genet. 32(11), 1797\u20131813 (2023)","journal-title":"Hum. Mol. Genet."},{"issue":"1","key":"14_CR16","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1111\/ene.13439","volume":"25","author":"CA Lane","year":"2018","unstructured":"Lane, C.A., Hardy, J., Schott, J.M.: Alzheimer\u2019s disease. Eur. J. Neurol. 25(1), 59\u201370 (2018). https:\/\/doi.org\/10.1111\/ene.13439","journal-title":"Eur. J. Neurol."},{"issue":"14","key":"14_CR17","doi-asserted-by":"publisher","first-page":"4936","DOI":"10.1073\/pnas.0408031102","volume":"102","author":"M Levine","year":"2005","unstructured":"Levine, M., Davidson, E.H.: Gene regulatory networks for development. Proc. Natl. Acad. Sci. 102(14), 4936\u20134942 (2005)","journal-title":"Proc. Natl. Acad. Sci."},{"doi-asserted-by":"crossref","unstructured":"Littman, R., Cheng, M., Wang, N., Peng, C., Yang, X.: SCING: inference of robust, interpretable gene regulatory networks from single cell and spatial transcriptomics. Iscience 26(7) (2023)","key":"14_CR18","DOI":"10.1016\/j.isci.2023.107124"},{"key":"14_CR19","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2016.00378","volume":"7","author":"B Ma","year":"2016","unstructured":"Ma, B., Hottiger, M.O.: Crosstalk between WNT\/$$\\beta $$-catenin and NF-$$\\kappa $$b signaling pathway during inflammation. Front. Immunol. 7, 221254 (2016)","journal-title":"Front. Immunol."},{"issue":"8","key":"14_CR20","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1038\/nmeth.2016","volume":"9","author":"D Marbach","year":"2012","unstructured":"Marbach, D., et al.: Wisdom of crowds for robust gene network inference. Nat. Methods 9(8), 796\u2013804 (2012)","journal-title":"Nat. Methods"},{"doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., Melville, J.: UMAP: uniform manifold approximation and projection for dimension reduction. arXiv preprint (2018)","key":"14_CR21","DOI":"10.21105\/joss.00861"},{"issue":"11","key":"14_CR22","doi-asserted-by":"publisher","first-page":"7355","DOI":"10.1007\/s12035-019-1605-3","volume":"56","author":"LM de Medeiros","year":"2019","unstructured":"de Medeiros, L.M., De Bastiani, M.A., Rico, E.P., Schonhofen, P., et al.: Cholinergic differentiation of human neuroblastoma SH-SY5Y cell line and its potential use as an in vitro model for Alzheimer\u2019s disease studies. Mol. Neurobiol. 56(11), 7355\u20137367 (2019)","journal-title":"Mol. Neurobiol."},{"issue":"5","key":"14_CR23","doi-asserted-by":"publisher","first-page":"1553","DOI":"10.1093\/bioinformatics\/btz781","volume":"36","author":"P Mignone","year":"2020","unstructured":"Mignone, P., Pio, G., D\u2019Elia, D., Ceci, M.: Exploiting transfer learning for the reconstruction of the human gene regulatory network. Bioinformatics 36(5), 1553\u20131561 (2020)","journal-title":"Bioinformatics"},{"doi-asserted-by":"publisher","unstructured":"Miller, J.A., et\u00a0al.: Neuropathological and transcriptomic characteristics of the aged brain. eLife 6, e31126 (2017). https:\/\/doi.org\/10.7554\/eLife.31126","key":"14_CR24","DOI":"10.7554\/eLife.31126"},{"key":"14_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artint.2018.07.007","volume":"267","author":"T Miller","year":"2019","unstructured":"Miller, T.: Explanation in artificial intelligence: insights from the social sciences. Artif. Intell. 267, 1\u201338 (2019)","journal-title":"Artif. Intell."},{"unstructured":"Molnar, C.: Interpretable Machine Learning, 2 edn. (2022). https:\/\/christophm.github.io\/interpretable-ml-book","key":"14_CR26"},{"key":"14_CR27","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.58029","volume":"9","author":"S Mukherjee","year":"2020","unstructured":"Mukherjee, S., Chaturvedi, P., Rankin, S.A., Fish, M.B., et al.: Sox17 and $$\\beta $$-catenin co-occupy WNT-responsive enhancers to govern the endoderm gene regulatory network. Elife 9, e58029 (2020)","journal-title":"Elife"},{"issue":"3","key":"14_CR28","doi-asserted-by":"publisher","first-page":"526","DOI":"10.3390\/biom13030526","volume":"13","author":"S Peignier","year":"2023","unstructured":"Peignier, S., Calevro, F.: Gene self-expressive networks as a generalization-aware tool to model gene regulatory networks. Biomolecules 13(3), 526 (2023)","journal-title":"Biomolecules"},{"issue":"04","key":"14_CR29","doi-asserted-by":"publisher","first-page":"2150022","DOI":"10.1142\/S0218213021500226","volume":"30","author":"S Peignier","year":"2021","unstructured":"Peignier, S., Schmitt, P., Calevro, F.: Data-driven gene regulatory networks inference based on classification algorithms. Int. J. Artif. Intell. Tools 30(04), 2150022 (2021)","journal-title":"Int. J. Artif. Intell. Tools"},{"issue":"2","key":"14_CR30","doi-asserted-by":"publisher","first-page":"269","DOI":"10.3390\/genes14020269","volume":"14","author":"P Schmitt","year":"2023","unstructured":"Schmitt, P., Sorin, B., Frout\u00e9, T., Parisot, N., et al.: GReNaDine: a data-driven Python library to infer gene regulatory networks from gene expression data. Genes 14(2), 269 (2023)","journal-title":"Genes"},{"doi-asserted-by":"crossref","unstructured":"Sebastian, S., Roy, S., Kalita, J.: A generic parallel framework for inferring large-scale gene regulatory networks from expression profiles: application to Alzheimer\u2019s disease network. Briefings Bioinf. 24(1), bbac482 (2023)","key":"14_CR31","DOI":"10.1093\/bib\/bbac482"},{"doi-asserted-by":"crossref","unstructured":"Shen, W.K., Chen, S.Y., Gan, Z.Q., Zhang, Y.Z., et\u00a0al.: AnimalTFDB 4.0: a comprehensive animal transcription factor database updated with variation and expression annotations. Nucleic Acids Res. 51, D39\u2013D45 (2023)","key":"14_CR32","DOI":"10.1093\/nar\/gkac907"},{"issue":"1","key":"14_CR33","doi-asserted-by":"publisher","first-page":"11295","DOI":"10.1038\/ncomms11295","volume":"7","author":"K Srinivasan","year":"2016","unstructured":"Srinivasan, K., Friedman, B.A., Larson, J.L., Lauffer, B.E., et al.: Untangling the brain\u2019s neuroinflammatory and neurodegenerative transcriptional responses. Nat. Commun. 7(1), 11295 (2016)","journal-title":"Nat. Commun."},{"issue":"43","key":"14_CR34","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., Mukherjee, S., et al.: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. 102(43), 15545\u201315550 (2005). https:\/\/doi.org\/10.1073\/pnas.0506580102","journal-title":"Proc. Natl. Acad. Sci."},{"doi-asserted-by":"publisher","unstructured":"Sun, B., Feng, J., Saenko, K.: Correlation alignment for unsupervised domain adaptation. arXiv e-prints arXiv:1612.01939 (2016). https:\/\/doi.org\/10.48550\/arXiv.1612.01939","key":"14_CR35","DOI":"10.48550\/arXiv.1612.01939"},{"issue":"16","key":"14_CR36","doi-asserted-by":"publisher","first-page":"8972","DOI":"10.3390\/ijms23168972","volume":"23","author":"E Sun","year":"2022","unstructured":"Sun, E., Motolani, A., Campos, L., Lu, T.: The pivotal role of NF-KB in the pathogenesis and therapeutics of Alzheimer\u2019s disease. Int. J. Mol. Sci. 23(16), 8972 (2022)","journal-title":"Int. J. Mol. Sci."},{"issue":"7965","key":"14_CR37","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1038\/s41586-023-06139-9","volume":"618","author":"CV Theodoris","year":"2023","unstructured":"Theodoris, C.V., Xiao, L., Chopra, A., Chaffin, M.D., et al.: Transfer learning enables predictions in network biology. Nature 618(7965), 616\u2013624 (2023)","journal-title":"Nature"},{"issue":"1","key":"14_CR38","doi-asserted-by":"publisher","first-page":"39921","DOI":"10.1038\/srep39921","volume":"7","author":"PY Tung","year":"2017","unstructured":"Tung, P.Y., Blischak, J.D., Hsiao, C.J., Knowles, D.A., et al.: Batch effects and the effective design of single-cell gene expression studies. Sci. Rep. 7(1), 39921 (2017)","journal-title":"Sci. Rep."},{"issue":"8","key":"14_CR39","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0006779","volume":"4","author":"M Uhrig","year":"2009","unstructured":"Uhrig, M., Ittrich, C., Wiedmann, V., Knyazev, Y., et al.: New Alzheimer amyloid $$\\beta $$ responsive genes identified in human neuroblastoma cells by hierarchical clustering. PLoS ONE 4(8), e6779 (2009)","journal-title":"PLoS ONE"},{"doi-asserted-by":"crossref","unstructured":"Wang, X.D., Liu, S., Lu, H., Guan, Y., et\u00a0al.: Analysis of shared genetic regulatory networks for Alzheimer\u2019s disease and epilepsy. BioMed Res. Int. (2021)","key":"14_CR40","DOI":"10.1155\/2021\/6692974"},{"issue":"7","key":"14_CR41","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0101850","volume":"9","author":"N Ward","year":"2014","unstructured":"Ward, N., Moreno-Hagelsieb, G.: Quickly finding orthologs as reciprocal best hits with BLAT, LAST, and UBLAST: how much do we miss? PLoS ONE 9(7), e101850 (2014). https:\/\/doi.org\/10.1371\/journal.pone.0101850","journal-title":"PLoS ONE"},{"issue":"1","key":"14_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss, K., Khoshgoftaar, T.M., Wang, D.D.: A survey of transfer learning. J. Big Data 3(1), 1\u201340 (2016). https:\/\/doi.org\/10.1186\/s40537-016-0043-6","journal-title":"J. Big Data"},{"key":"14_CR43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-017-1382-0","volume":"19","author":"FA Wolf","year":"2018","unstructured":"Wolf, F.A., Angerer, P., Theis, F.J.: SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 1\u20135 (2018)","journal-title":"Genome Biol."},{"issue":"3","key":"14_CR44","doi-asserted-by":"publisher","first-page":"249","DOI":"10.3109\/08830185.2012.755176","volume":"32","author":"Y Yang","year":"2013","unstructured":"Yang, Y., Bazhin, A.V., Werner, J., Karakhanova, S.: Reactive oxygen species in the immune system. Int. Rev. Immunol. 32(3), 249\u2013270 (2013)","journal-title":"Int. Rev. Immunol."},{"doi-asserted-by":"crossref","unstructured":"Yiannopoulou, K.G., Papageorgiou, S.G.: Current and future treatments in Alzheimer disease: an update. J. Central Nerv. Syst. Dis. 12 (2020)","key":"14_CR45","DOI":"10.1177\/1179573520907397"},{"issue":"2","key":"14_CR46","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1109\/JAS.2022.106004","volume":"10","author":"W Zhang","year":"2022","unstructured":"Zhang, W., Deng, L., Zhang, L., Wu, D.: A survey on negative transfer. IEEE\/CAA J. Automatica Sinica 10(2), 305\u2013329 (2022)","journal-title":"IEEE\/CAA J. Automatica Sinica"},{"issue":"1","key":"14_CR47","doi-asserted-by":"publisher","first-page":"14049","DOI":"10.1038\/ncomms14049","volume":"8","author":"GX Zheng","year":"2017","unstructured":"Zheng, G.X., Terry, J.M., Belgrader, P., Ryvkin, P., et al.: Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8(1), 14049 (2017)","journal-title":"Nat. Commun."},{"unstructured":"Zhou, D., Bousquet, O., Lal, T., Weston, J., Sch\u00f6lkopf, B.: Learning with local and global consistency. In: Advances in Neural Information Processing Systems, vol. 16 (2003)","key":"14_CR48"}],"container-title":["Lecture Notes in Computer Science","Computational Methods in Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-01436-8_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T15:14:46Z","timestamp":1757430886000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-01436-8_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"ISBN":["9783032014351","9783032014368"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-01436-8_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"19 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CMSB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Methods in Systems Biology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cmsb2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cmsb2025.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}