{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T04:37:51Z","timestamp":1772771871320,"version":"3.50.1"},"reference-count":62,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Fujian Province Foundation","award":["2020Y4001"],"award-info":[{"award-number":["2020Y4001"]}]},{"name":"Foundation of Education Department of Liaoning Province","award":["LJKZ0280"],"award-info":[{"award-number":["LJKZ0280"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11874310"],"award-info":[{"award-number":["11874310"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12090052"],"award-info":[{"award-number":["12090052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021ZD0201900"],"award-info":[{"award-number":["2021ZD0201900"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The proliferation of single-cell multimodal sequencing technologies has enabled us to understand cellular heterogeneity with multiple views, providing novel and actionable biological insights into the disease-driving mechanisms. Here, we propose a comprehensive end-to-end single-cell multimodal analysis framework named Deep Parametric Inference (DPI). DPI transforms single-cell multimodal data into a multimodal parameter space by inferring individual modal parameters. Analysis of cord blood mononuclear cells (CBMC) reveals that the multimodal parameter space can characterize the heterogeneity of cells more comprehensively than individual modalities. Furthermore, comparisons with the state-of-the-art methods on multiple datasets show that DPI has superior performance. Additionally, DPI can reference and query cell types without batch effects. As a result, DPI can successfully analyze the progression of COVID-19 disease in peripheral blood mononuclear cells (PBMC). Notably, we further propose a cell state vector field and analyze the transformation pattern of bone marrow cells (BMC) states. In conclusion, DPI is a powerful single-cell multimodal analysis framework that can provide new biological insights into biomedical researchers. The python packages, datasets and user-friendly manuals of DPI are freely available at https:\/\/linproxy.fan.workers.dev:443\/https\/github.com\/studentiz\/dpi.<\/jats:p>","DOI":"10.1093\/bib\/bbad005","type":"journal-article","created":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T00:26:35Z","timestamp":1673828795000},"source":"Crossref","is-referenced-by-count":58,"title":["Modeling and analyzing single-cell multimodal data with deep parametric inference"],"prefix":"10.1093","volume":"24","author":[{"given":"Huan","family":"Hu","sequence":"first","affiliation":[{"name":"Xiamen University Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, , Xiamen 361005 , China"},{"name":"Xiamen University National Institute for Data Science in Health and Medicine, and State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, , Xiamen 36100 5 China"},{"name":"Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), and Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Zhejiang 325001 , China"}]},{"given":"Zhen","family":"Feng","sequence":"additional","affiliation":[{"name":"Wenzhou Medical University First Affiliated Hospital of Wenzhou Medical University, , Wenzhou 325000 , China"}]},{"given":"Hai","family":"Lin","sequence":"additional","affiliation":[{"name":"Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), and Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Zhejiang 325001 , China"}]},{"given":"Junjie","family":"Zhao","sequence":"additional","affiliation":[{"name":"Guangzhou University Cyberspace Institute of Advanced Technology, , Guangzhou 510000 , China"}]},{"given":"Yaru","family":"Zhang","sequence":"additional","affiliation":[{"name":"Wenzhou Medical University Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, , Wenzhou 325027 , China"}]},{"given":"Fei","family":"Xu","sequence":"additional","affiliation":[{"name":"Xiamen University Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, , Xiamen 361005 , China"}]},{"given":"Lingling","family":"Chen","sequence":"additional","affiliation":[{"name":"Xiamen University Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, , Xiamen 361005 , China"}]},{"given":"Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"Xiamen University Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, , Xiamen 361005 , China"}]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-1299-4802","authenticated-orcid":false,"given":"Yunlong","family":"Ma","sequence":"additional","affiliation":[{"name":"Wenzhou Medical University Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, , Wenzhou 325027 , China"}]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-1172-7411","authenticated-orcid":false,"given":"Jianzhong","family":"Su","sequence":"additional","affiliation":[{"name":"Wenzhou Medical University Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, , Wenzhou 325027 , China"}]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0001-9713-1864","authenticated-orcid":false,"given":"Qi","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Science and Technology Liaoning School of Computer Science and Software Engineering, , Anshan 114051 , China"}]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-8712-0544","authenticated-orcid":false,"given":"Jianwei","family":"Shuai","sequence":"additional","affiliation":[{"name":"Xiamen University Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, , Xiamen 361005 , China"},{"name":"Xiamen University National Institute for Data Science in Health and Medicine, and State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, , Xiamen 36100 5 China"},{"name":"Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), and Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Zhejiang 325001 , China"}]}],"member":"286","published-online":{"date-parts":[[2023,1,14]]},"reference":[{"key":"2023011917084635100_ref1","doi-asserted-by":"crossref","first-page":"eabf1970","DOI":"10.1126\/science.abf1970","article-title":"Single-cell RNA-seq reveals cell type\u2013specific molecular and genetic associations to lupus","volume":"376","author":"Perez","year":"2022","journal-title":"Science"},{"key":"2023011917084635100_ref2","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1038\/s41593-022-01022-8","article-title":"Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain","volume":"25","author":"Marsh","year":"2022","journal-title":"Nat Neurosci"},{"key":"2023011917084635100_ref3","doi-asserted-by":"crossref","first-page":"103982","DOI":"10.1016\/j.isci.2022.103982","article-title":"Dormant Nfatc1 reporter-marked basal stem\/progenitor cells contribute to mammary lobuloalveoli formation","volume":"25","author":"Liu","year":"2022","journal-title":"iScience"},{"key":"2023011917084635100_ref4","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac234","article-title":"Cell-cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies","volume":"23","author":"Peng","year":"2022","journal-title":"Brief Bioinform"},{"key":"2023011917084635100_ref5","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/s41587-021-01131-y","article-title":"Single-cell immunology of SARS-CoV-2 infection","volume":"40","author":"Tian","year":"2022","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref6","doi-asserted-by":"crossref","first-page":"105119","DOI":"10.1016\/j.compbiomed.2021.105119","article-title":"VDA-RWLRLS: an anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares","volume":"140","author":"Shen","year":"2022","journal-title":"Comput Biol Med"},{"key":"2023011917084635100_ref7","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1038\/nmeth.4380","article-title":"Simultaneous epitope and transcriptome measurement in single cells","volume":"14","author":"Stoeckius","year":"2017","journal-title":"Nat Methods"},{"key":"2023011917084635100_ref8","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1038\/nbt.3973","article-title":"Multiplexed quantification of proteins and transcripts in single cells","volume":"35","author":"Peterson","year":"2017","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref9","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1038\/nmeth.4488","article-title":"Single-cell RNA-seq\u2014now with protein","volume":"14","author":"Todorovic","year":"2017","journal-title":"Nat Methods"},{"key":"2023011917084635100_ref10","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1038\/s41587-021-00927-2","article-title":"Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells","volume":"39","author":"Mimitou","year":"2021","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref11","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41587-020-0645-6","article-title":"Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling","volume":"39","author":"Lareau","year":"2021","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref12","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1038\/s41592-019-0392-0","article-title":"Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells","volume":"16","author":"Mimitou","year":"2019","journal-title":"Nat Methods"},{"key":"2023011917084635100_ref13","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1038\/s41592-021-01245-w","article-title":"Arsenal of single-cell multi-omics methods expanded","volume":"18","author":"Tang","year":"2021","journal-title":"Nat Methods"},{"key":"2023011917084635100_ref14","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive integration of single-cell data","volume":"177","author":"Stuart","year":"2019","journal-title":"Cell"},{"key":"2023011917084635100_ref15","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1186\/s13059-020-02015-1","article-title":"MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data","volume":"21","author":"Argelaguet","year":"2020","journal-title":"Genome Biol"},{"key":"2023011917084635100_ref16","doi-asserted-by":"crossref","first-page":"5814","DOI":"10.1093\/nar\/gkaa314","article-title":"BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data","volume":"48","author":"Wang","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2023011917084635100_ref17","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1186\/s13059-021-02313-2","article-title":"Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities","volume":"22","author":"Singh","year":"2021","journal-title":"Genome Biol"},{"key":"2023011917084635100_ref18","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"key":"2023011917084635100_ref19","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1080\/15476286.2022.2027151","article-title":"CITEMO(XMBD): a flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells","volume":"19","author":"Hu","year":"2022","journal-title":"RNA Biol"},{"key":"2023011917084635100_ref20","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1038\/s41592-020-01050-x","article-title":"Joint probabilistic modeling of single-cell multi-omic data with TotalVI","volume":"18","author":"Gayoso","year":"2021","journal-title":"Nat Methods"},{"key":"2023011917084635100_ref21","article-title":"Multigrate: single-cell multi-omic data integration","author":"Lotfollahi","year":"2022","journal-title":"BioRxiv"},{"key":"2023011917084635100_ref22","article-title":"UMINT: unsupervised neural network for single cell multi-omics integration","author":"Maitra","year":"2022","journal-title":"BioRxiv"},{"key":"2023011917084635100_ref23","doi-asserted-by":"crossref","DOI":"10.1038\/s41587-022-01284-4","article-title":"Multi-omics single-cell data integration and regulatory inference with graph-linked embedding","volume":"40","author":"Cao","year":"2022","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref24","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1038\/s41467-018-07931-2","article-title":"Single-cell RNA-seq denoising using a deep count autoencoder","volume":"10","author":"Eraslan","year":"2019","journal-title":"Nat Commun"},{"key":"2023011917084635100_ref25","volume-title":"2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops","author":"Wang"},{"key":"2023011917084635100_ref26","volume-title":"In Proceedings of the 18th conference on Winter simulation (WSC '86)","author":"Devroye"},{"key":"2023011917084635100_ref27","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac266","article-title":"A deep learning method for predicting metabolite-disease associations via graph neural network","volume":"23","author":"Sun","year":"2022","journal-title":"Brief Bioinform"},{"key":"2023011917084635100_ref28","article-title":"Auto-encoding variational bayes","author":"Kingma","year":"2013"},{"key":"2023011917084635100_ref29","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1186\/s13059-015-0805-z","article-title":"ZIFA: dimensionality reduction for zero-inflated single-cell gene expression analysis","volume":"16","author":"Pierson","year":"2015","journal-title":"Genome Biol"},{"key":"2023011917084635100_ref30","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1038\/s41467-020-14976-9","article-title":"Embracing the dropouts in single-cell RNA-seq analysis","volume":"11","author":"Qiu","year":"2020","journal-title":"Nat Commun"},{"key":"2023011917084635100_ref31","article-title":"Evaluating the performance of dropout imputation and clustering methods for single-cell RNA sequencing data","volume":"11","author":"Xu","year":"2022","journal-title":"Comput Biol Med"},{"key":"2023011917084635100_ref32","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1038\/s41587-020-0591-3","article-title":"Generalizing RNA velocity to transient cell states through dynamical modeling","volume":"38","author":"Bergen","year":"2020","journal-title":"Nat Biotechnol"},{"key":"2023011917084635100_ref33","doi-asserted-by":"crossref","first-page":"e46045","DOI":"10.7554\/eLife.46045","article-title":"Circulating T cell-monocyte complexes are markers of immune perturbations","volume":"8","author":"Burel","year":"2019","journal-title":"Elife"},{"key":"2023011917084635100_ref34","first-page":"1","article-title":"A dendrite method for cluster analysis","volume":"3","author":"Cali\u0144ski","year":"1974","journal-title":"Commun Stat"},{"key":"2023011917084635100_ref35","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","article-title":"Silhouettes: a graphical aid to the interpretation and validation of cluster analysis","volume":"20","author":"Rousseeuw","year":"1987","journal-title":"J Comput Appl Math"},{"key":"2023011917084635100_ref36","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/TPAMI.1979.4766909","article-title":"A cluster separation measure","volume":"PAMI-1","author":"Davies","year":"1979","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2023011917084635100_ref37","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1037\/1082-989X.9.3.386","article-title":"Properties of the Hubert-Arabie adjusted Rand index","volume":"9","author":"Steinley","year":"2004","journal-title":"Psychol Methods"},{"key":"2023011917084635100_ref38","volume":"11","author":"Vinh","journal-title":"J. Mach. Learn. Res"},{"key":"2023011917084635100_ref39","doi-asserted-by":"crossref","first-page":"eabl9464","DOI":"10.1126\/sciimmunol.abl9464","article-title":"SARS-CoV-2 epitope-specific CD4+ memory T cell responses across COVID-19 disease severity and antibody durability","volume":"7","author":"Nelson","year":"2022","journal-title":"Sci Immunol"},{"key":"2023011917084635100_ref40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-022-30913-4","article-title":"Expansion of cytotoxic tissue-resident CD8+ T cells and CCR6+ CD161+ CD4+ T cells in the nasal mucosa following mRNA COVID-19 vaccination","volume":"13","author":"Ssemaganda","year":"2022","journal-title":"Nat Commun"},{"key":"2023011917084635100_ref41","doi-asserted-by":"crossref","DOI":"10.1164\/rccm.202111-2493OC","article-title":"CD4+ T cell dysfunction in severe COVID-19 disease is TNF\u03b1\/TNFRI-dependent","volume":"205","author":"Popescu","year":"2022","journal-title":"Am J Respir Crit Care Med"},{"key":"2023011917084635100_ref42","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1093\/hmg\/ddab125","article-title":"Integrative genomics analysis reveals a 21q22.11 locus contributing risk to COVID-19","volume":"30","author":"Ma","year":"2021","journal-title":"Hum Mol Genet"},{"key":"2023011917084635100_ref43","doi-asserted-by":"crossref","first-page":"101410","DOI":"10.1016\/j.arr.2021.101410","article-title":"Targeting immune dysfunction in aging","volume":"70","author":"Borgoni","year":"2021","journal-title":"Ageing Res Rev"},{"key":"2023011917084635100_ref44","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1016\/j.cell.2020.10.001","article-title":"Imbalance of regulatory and cytotoxic SARS-CoV-2-reactive CD4+ T cells in COVID-19","volume":"183","author":"Meckiff","year":"2020","journal-title":"Cell"},{"key":"2023011917084635100_ref45","doi-asserted-by":"crossref","first-page":"6489","DOI":"10.4049\/jimmunol.175.10.6489","article-title":"Stepwise differentiation of CD4 memory T cells defined by expression of CCR7 and CD27","volume":"175","author":"Fritsch","year":"2005","journal-title":"J Immunol"},{"key":"2023011917084635100_ref46","doi-asserted-by":"crossref","first-page":"1258","DOI":"10.1016\/j.immuni.2020.11.016","article-title":"Low-avidity CD4+ T cell responses to SARS-CoV-2 in unexposed individuals and humans with severe COVID-19","volume":"53","author":"Bacher","year":"2020","journal-title":"Immunity"},{"key":"2023011917084635100_ref47","doi-asserted-by":"crossref","first-page":"154652","DOI":"10.1016\/j.scitotenv.2022.154652","article-title":"Smoking related environmental microbes affecting the pulmonary microbiome in Chinese population","volume":"829","author":"Liu","year":"2022","journal-title":"Sci Total Environ"},{"key":"2023011917084635100_ref48","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1002\/iid3.526","article-title":"TIM-3 as a potential exhaustion marker in CD4+ T cells of COVID-19 patients","volume":"9","author":"Modabber","year":"2021","journal-title":"Immun Inflamm Dis"},{"key":"2023011917084635100_ref49","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1038\/s41423-020-0401-3","article-title":"Elevated exhaustion levels and reduced functional diversity of T cells in peripheral blood may predict severe progression in COVID-19 patients","volume":"17","author":"Zheng","year":"2020","journal-title":"Cell Mol Immunol"},{"key":"2023011917084635100_ref50","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1016\/j.humimm.2014.04.006","article-title":"Autoimmune manifestations in SCID due to IL7R mutations: Omenn syndrome and cytopenias","volume":"75","author":"Zago","year":"2014","journal-title":"Hum Immunol"},{"key":"2023011917084635100_ref51","doi-asserted-by":"crossref","DOI":"10.1016\/j.autrev.2022.103120","article-title":"Significance of IL-7 and IL-7R in RA and autoimmunity","volume":"21","author":"Meyer","year":"2022","journal-title":"Autoimmun Rev"},{"key":"2023011917084635100_ref52","doi-asserted-by":"crossref","first-page":"1533","DOI":"10.1038\/s41375-022-01590-5","article-title":"Mutant IL7R collaborates with MYC to induce T-cell acute lymphoblastic leukemia","volume":"36","author":"Oliveira","year":"2022","journal-title":"Leukemia"},{"key":"2023011917084635100_ref53","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.jaci.2020.10.020","article-title":"SCID newborn screening: what we\u2019ve learned","volume":"147","author":"Currier","year":"2021","journal-title":"J Allergy Clin Immunol"},{"key":"2023011917084635100_ref54","first-page":"1","article-title":"Immune disease risk variants regulate gene expression dynamics during CD4+ T cell activation","author":"Soskic","year":"2022","journal-title":"Nat Genet"},{"key":"2023011917084635100_ref55","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1136\/jclinpath-2020-206927","article-title":"Protein tyrosine phosphatase receptor type C (PTPRC or CD45)","volume":"74","author":"Al Barashdi","year":"2021","journal-title":"J Clin Pathol"},{"key":"2023011917084635100_ref56","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1007\/s12016-015-8498-3","article-title":"OX40, OX40L and autoimmunity: a comprehensive review","volume":"50","author":"Webb","year":"2016","journal-title":"Clin Rev Allergy Immunol"},{"key":"2023011917084635100_ref57","doi-asserted-by":"crossref","first-page":"5990","DOI":"10.4049\/jimmunol.181.9.5990","article-title":"OX40 costimulatory signals potentiate the memory commitment of effector CD8+ T cells","volume":"181","author":"Mousavi","year":"2008","journal-title":"J Immunol"},{"key":"2023011917084635100_ref58","doi-asserted-by":"crossref","first-page":"5975","DOI":"10.4049\/jimmunol.176.10.5975","article-title":"OX40-OX40 ligand interaction through T cell-T cell contact contributes to CD4 T cell longevity","volume":"176","author":"Soroosh","year":"2006","journal-title":"J Immunol"},{"key":"2023011917084635100_ref59","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/978-981-32-9717-3_3","article-title":"The TNF-TNFR family of co-signal molecules","volume":"1189","author":"So","year":"2019","journal-title":"Adv Exp Med Biol"},{"key":"2023011917084635100_ref60","first-page":"9838341","article-title":"Caspase-1 and Gasdermin D afford the optimal targets with distinct switching strategies in NLRP1b Inflammasome-induced cell death","volume":"2022","author":"Li","year":"2022","journal-title":"Research (Wash D C)"},{"key":"2023011917084635100_ref61","doi-asserted-by":"crossref","first-page":"726638","DOI":"10.3389\/fphy.2021.726638","article-title":"Oscillations governed by the incoherent dynamics in necroptotic signaling","volume":"9","author":"Xu","year":"2021","journal-title":"Front Phys"},{"key":"2023011917084635100_ref62","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1007\/s13238-020-00810-x","article-title":"RIP1-dependent linear and nonlinear recruitments of caspase-8 and RIP3 respectively to necrosome specify distinct cell death outcomes","volume":"12","author":"Li","year":"2021","journal-title":"Protein Cell"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbad005\/48782564\/bbad005.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbad005\/48782564\/bbad005.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T17:19:08Z","timestamp":1674148748000},"score":1,"resource":{"primary":{"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbad005\/6987655"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,19]]}},"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/doi.org\/10.1093\/bib\/bbad005","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,1]]},"published":{"date-parts":[[2023,1]]},"article-number":"bbad005"}}