SpateCV: cross-modality alignment regularization of cell types improves spatial gene imputation for spatial transcriptomics

Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding si...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Journal of translational medicine Ročník 23; číslo 1; s. 1188 - 21
Hlavní autori:	Yuan, Jiaqi, Yu, Junhua, Yi, Qianbei, Ye, Zheng, Xu, Peng, Liu, Wenbin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 29.10.2025 BioMed Central Ltd BMC
Predmet:	Anopheles Attention mechanism Biomedical and Life Sciences Biomedicine Cancer microenvironment Conditional variational autoencoder (CVAE) Gene imputation Gene mutations Genes Genetic research Genetic transcription Genomics Health aspects Identification and classification Medicine/Public Health Methods Neural networks Neurons RNA sequencing Single-cell RNA sequencing Spatial transcriptomics Technology application China Attention mechanism Conditional variational autoencoder (CVAE) Spatial transcriptomics Single-cell RNA sequencing Gene imputation
ISSN:	1479-5876, 1479-5876
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding similar cells with consistent representations from the two types of data. Methods In this paper, we construct a conditional variational autoencoder (CVAE) architecture, named SpateCV, to explicitly regularize the embedding alignment of similar cells from scRNA-seq and ST data in a shared latent through a clustering loss. Results Benchmark results across twelve datasets demonstrate that SpateCV achieves superior performance in spatial gene imputation and spatial patterns reconstruction. Critically, SpateCV translates this technical accuracy into biological insight. With the imputed genome-wide expression, our method enables the identification of novel spatially differentially expressed genes, such as the astrocyte marker Hepacam, and facilitates the inference of layer-specific intercellular communication networks, identifying corpus callosum cells as key signaling hubs in the mouse visual cortex. Additionally, SpateCV enables the in silico spatial mapping of neuronal subtypes by integrating spatial context into scRNA-seq data. Conclusion SpateCV provides a robust framework for extracting biological knowledge from multimodal spatial-omics data.
AbstractList	Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding similar cells with consistent representations from the two types of data. Methods In this paper, we construct a conditional variational autoencoder (CVAE) architecture, named SpateCV, to explicitly regularize the embedding alignment of similar cells from scRNA-seq and ST data in a shared latent through a clustering loss. Results Benchmark results across twelve datasets demonstrate that SpateCV achieves superior performance in spatial gene imputation and spatial patterns reconstruction. Critically, SpateCV translates this technical accuracy into biological insight. With the imputed genome-wide expression, our method enables the identification of novel spatially differentially expressed genes, such as the astrocyte marker Hepacam, and facilitates the inference of layer-specific intercellular communication networks, identifying corpus callosum cells as key signaling hubs in the mouse visual cortex. Additionally, SpateCV enables the in silico spatial mapping of neuronal subtypes by integrating spatial context into scRNA-seq data. Conclusion SpateCV provides a robust framework for extracting biological knowledge from multimodal spatial-omics data. The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding similar cells with consistent representations from the two types of data. In this paper, we construct a conditional variational autoencoder (CVAE) architecture, named SpateCV, to explicitly regularize the embedding alignment of similar cells from scRNA-seq and ST data in a shared latent through a clustering loss. Benchmark results across twelve datasets demonstrate that SpateCV achieves superior performance in spatial gene imputation and spatial patterns reconstruction. Critically, SpateCV translates this technical accuracy into biological insight. With the imputed genome-wide expression, our method enables the identification of novel spatially differentially expressed genes, such as the astrocyte marker Hepacam, and facilitates the inference of layer-specific intercellular communication networks, identifying corpus callosum cells as key signaling hubs in the mouse visual cortex. Additionally, SpateCV enables the in silico spatial mapping of neuronal subtypes by integrating spatial context into scRNA-seq data. SpateCV provides a robust framework for extracting biological knowledge from multimodal spatial-omics data. Abstract Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding similar cells with consistent representations from the two types of data. Methods In this paper, we construct a conditional variational autoencoder (CVAE) architecture, named SpateCV, to explicitly regularize the embedding alignment of similar cells from scRNA-seq and ST data in a shared latent through a clustering loss. Results Benchmark results across twelve datasets demonstrate that SpateCV achieves superior performance in spatial gene imputation and spatial patterns reconstruction. Critically, SpateCV translates this technical accuracy into biological insight. With the imputed genome-wide expression, our method enables the identification of novel spatially differentially expressed genes, such as the astrocyte marker Hepacam, and facilitates the inference of layer-specific intercellular communication networks, identifying corpus callosum cells as key signaling hubs in the mouse visual cortex. Additionally, SpateCV enables the in silico spatial mapping of neuronal subtypes by integrating spatial context into scRNA-seq data. Conclusion SpateCV provides a robust framework for extracting biological knowledge from multimodal spatial-omics data. Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue architecture and cellular heterogeneity simultaneously. The key to accomplishing this goal mainly relies on effectively co-embedding similar cells with consistent representations from the two types of data. Methods In this paper, we construct a conditional variational autoencoder (CVAE) architecture, named SpateCV, to explicitly regularize the embedding alignment of similar cells from scRNA-seq and ST data in a shared latent through a clustering loss. Results Benchmark results across twelve datasets demonstrate that SpateCV achieves superior performance in spatial gene imputation and spatial patterns reconstruction. Critically, SpateCV translates this technical accuracy into biological insight. With the imputed genome-wide expression, our method enables the identification of novel spatially differentially expressed genes, such as the astrocyte marker Hepacam, and facilitates the inference of layer-specific intercellular communication networks, identifying corpus callosum cells as key signaling hubs in the mouse visual cortex. Additionally, SpateCV enables the in silico spatial mapping of neuronal subtypes by integrating spatial context into scRNA-seq data. Conclusion SpateCV provides a robust framework for extracting biological knowledge from multimodal spatial-omics data. Keywords: Spatial transcriptomics, Single-cell RNA sequencing, Gene imputation, Conditional variational autoencoder (CVAE), Attention mechanism
ArticleNumber	1188
Audience	Academic
Author	Xu, Peng Ye, Zheng Yu, Junhua Liu, Wenbin Yuan, Jiaqi Yi, Qianbei
Author_xml	– sequence: 1 givenname: Jiaqi surname: Yuan fullname: Yuan, Jiaqi organization: Institute of Computational Science and Technology, Guangzhou University – sequence: 2 givenname: Junhua surname: Yu fullname: Yu, Junhua organization: Institute of Computational Science and Technology, Guangzhou University – sequence: 3 givenname: Qianbei surname: Yi fullname: Yi, Qianbei organization: Institute of Computational Science and Technology, Guangzhou University – sequence: 4 givenname: Zheng surname: Ye fullname: Ye, Zheng email: zheng_ye@gzhu.edu.cn organization: Institute of Computational Science and Technology, Guangzhou University, School of Computer Science of Information Technology, Qiannan Normal University for Nationalities – sequence: 5 givenname: Peng surname: Xu fullname: Xu, Peng email: gdxupeng@gzhu.edu.cn organization: Institute of Computational Science and Technology, Guangzhou University, School of Computer Science of Information Technology, Qiannan Normal University for Nationalities – sequence: 6 givenname: Wenbin orcidid: 0000-0001-9091-3177 surname: Liu fullname: Liu, Wenbin email: wbliu6910@gzhu.edu.cn organization: Institute of Computational Science and Technology, Guangzhou University
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/41162996$$D View this record in MEDLINE/PubMed
BookMark	eNp9kk2LHCEQhpuwIfuR_IEcQkMuufRGbVvt3JYlHwsLOeTjKo5WNw7dOlE7MMmfT830ZkggBEGlfOrV8q3L6izEAFX1nJJrSpV4nSnrhWwI6xoiGcf5UXVBueybTklx9sf-vLrMeUsIQrx_Up1zSgXre3FR_fy0MwVuv76pbYo5N3N0ZvJlX-M8hhlCqROMy2SS_2GKj6GOQ21hmuqy30Gu_bxL8TtuMup4M9UjBDhEl7LiQ0yns5JMyDb5XYmzt_lp9XgwU4ZnD-tV9eXd28-3H5r7j-_vbm_uG8ulLE3LbctaSxVwA6AYt4IIY5jqNmIjhFFMOQak77hwHaHAQDnV0U5R5ZzqWXtV3a26Lpqt3iU_m7TX0Xh9DMQ0apOKtxNowzYCDOVuMIoba_EO4E6InnadUkOLWq9WLSz72wK56Nnnw3-YAHHJumUISzRGIvpyRUeDyj4MEeu3B1zfKEGlFJJ0SF3_g8LhAP8IDR88xv9KePHwgmUzgzvV89tTBNgKHB1NMJwQSvShcfTaOBobRx8bRxNMatekjHAYIeltXFJAW_6X9QtSyMXr
Cites_doi	10.1038/s41598-019-41695-z 10.1038/s41586-021-03705-x 10.1038/s41592-022-01480-9 10.1038/s41587-021-01001-7 10.1093/bib/bbae571 10.1007/s43032-024-01676-8 10.1038/nature05453 10.1038/s41467-020-20059-6 10.1038/s41467-020-15968-5 10.1126/science.aaa1934 10.1038/s41467-022-33758-z 10.1038/s41586-019-1049-y 10.1016/j.cell.2019.05.006 10.1186/s40364-025-00738-6 10.1093/nar/gkae409 10.1126/science.aat5691 10.1016/j.neuron.2023.05.032 10.1016/j.neuron.2016.10.001 10.1093/nar/gkaf158 10.1016/j.jhep.2005.01.025 10.1038/s41467-020-20343-5 10.1186/s13059-021-02556-z 10.1007/978-3-319-20828-2 10.1038/s41586-019-1506-7 10.1073/pnas.1912459116 10.1007/s00277-025-06387-x 10.1038/s41587-021-01006-2 10.1038/s41586-020-03126-2 10.1038/s41592-021-01336-8 10.1038/s41587-022-01448-2 10.1038/s41592-021-01264-7 10.1007/s11010-014-1991-9 10.1101/2021.04.16.440115 10.1101/576827 10.1038/s41587-021-00830-w 10.1016/j.cell.2018.02.001 10.1126/science.aau5324 10.1007/s10238-025-01751-7 10.1016/j.neuron.2021.05.025 10.1101/718395 10.1038/s41592-022-01575-3 10.61186/ijbc.16.2.84 10.1186/s12859-022-05003-3 10.1186/s13059-021-02565-y 10.1038/s41592-022-01728-4 10.1038/s41596-021-00573-7 10.1186/1750-1326-6-60 10.1101/2021.12.05.471303 10.1101/2020.08.27.268730 10.1016/j.mcn.2008.06.004 10.1126/sciadv.adq3350 10.1038/nmeth.2694 10.1016/j.cell.2019.05.031 10.1038/s41592-018-0229-2 10.1093/nar/gkac889 10.1038/s41587-024-02193-4
ContentType	Journal Article
Copyright	The Author(s) 2025 COPYRIGHT 2025 BioMed Central Ltd.
Copyright_xml	– notice: The Author(s) 2025 – notice: COPYRIGHT 2025 BioMed Central Ltd.
DBID	C6C AAYXX CITATION NPM 7X8 DOA
DOI	10.1186/s12967-025-07245-0
DatabaseName	Springer Nature OA Free Journals CrossRef PubMed MEDLINE - Academic DOAJ Directory of Open Access Journals
DatabaseTitle	CrossRef PubMed MEDLINE - Academic
DatabaseTitleList
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Medicine
EISSN	1479-5876
EndPage	21
ExternalDocumentID	oai_doaj_org_article_a2b6ea14dfa84acc85be4d66915588f3 A861776705 41162996 10_1186_s12967_025_07245_0
Genre	Journal Article
GeographicLocations	China
GeographicLocations_xml	– name: China
GroupedDBID	--- 0R~ 29L 2WC 53G 5VS 6PF 7X7 88E 8FI 8FJ AAFWJ AAJSJ AASML AAWTL ABDBF ABUWG ACGFO ACGFS ACIHN ACIWK ACPRK ACUHS ADBBV ADUKV AEAQA AENEX AFFHD AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BCNDV BENPR BFQNJ BMC BPHCQ BVXVI C6C CCPQU CS3 DIK DU5 E3Z EBD EBLON EBS ESX F5P FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR INH INR ITC KQ8 M1P M~E O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PJZUB PPXIY PQQKQ PROAC PSQYO RBZ RNS ROL RPM RSV SBL SOJ TR2 TUS UKHRP WOQ WOW XSB ~8M AAYXX CITATION NPM 7X8
ID	FETCH-LOGICAL-c477t-34c323c18e4aee824c606aa285b6b66a828d2e09546d501e2e8d8515818dd8923
IEDL.DBID	DOA
ISICitedReferencesCount	0
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001605844500005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1479-5876
IngestDate	Mon Nov 10 19:20:44 EST 2025 Thu Oct 30 17:10:31 EDT 2025 Sat Nov 29 13:45:44 EST 2025 Sat Nov 29 10:28:43 EST 2025 Mon Nov 03 02:05:55 EST 2025 Wed Nov 05 20:41:18 EST 2025 Thu Oct 30 01:15:43 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Attention mechanism Conditional variational autoencoder (CVAE) Spatial transcriptomics Single-cell RNA sequencing Gene imputation
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c477t-34c323c18e4aee824c606aa285b6b66a828d2e09546d501e2e8d8515818dd8923
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ORCID	0000-0001-9091-3177
OpenAccessLink	https://doaj.org/article/a2b6ea14dfa84acc85be4d66915588f3
PMID	41162996
PQID	3266971297
PQPubID	23479
PageCount	21
ParticipantIDs	doaj_primary_oai_doaj_org_article_a2b6ea14dfa84acc85be4d66915588f3 proquest_miscellaneous_3266971297 gale_infotracmisc_A861776705 gale_infotracacademiconefile_A861776705 pubmed_primary_41162996 crossref_primary_10_1186_s12967_025_07245_0 springer_journals_10_1186_s12967_025_07245_0
PublicationCentury	2000
PublicationDate	2025-10-29
PublicationDateYYYYMMDD	2025-10-29
PublicationDate_xml	– month: 10 year: 2025 text: 2025-10-29 day: 29
PublicationDecade	2020
PublicationPlace	London
PublicationPlace_xml	– name: London – name: England
PublicationTitle	Journal of translational medicine
PublicationTitleAbbrev	J Transl Med
PublicationTitleAlternate	J Transl Med
PublicationYear	2025
Publisher	BioMed Central BioMed Central Ltd BMC
Publisher_xml	– name: BioMed Central – name: BioMed Central Ltd – name: BMC
References	SCVD Brink (7245_CR18) 2020; 579 MD Luecken (7245_CR39) 2022; 19 MT Lorincz (7245_CR45) 2009; 40 7245_CR29 7245_CR25 7245_CR24 SA Aghapour (7245_CR3) 2024; 16 7245_CR27 7245_CR26 7245_CR21 P Rautenstrauch (7245_CR41) 2024; 52 7245_CR64 7245_CR23 7245_CR22 7245_CR66 B Li (7245_CR68) 2022; 19 Z Cang (7245_CR54) 2023; 20 SJ Wu (7245_CR57) 2023; 111 M Lotfollahi (7245_CR30) 2022; 40 DM Cable (7245_CR44) 2022; 19 T Lohoff (7245_CR60) 2022; 40 S Shah (7245_CR63) 2016; 92 7245_CR19 7245_CR5 7245_CR58 7245_CR16 7245_CR2 7245_CR15 7245_CR9 7245_CR10 T Stuart (7245_CR20) 2019; 177 7245_CR53 7245_CR56 7245_CR6 7245_CR11 7245_CR55 N Moriel (7245_CR14) 2021; 16 DM Cable (7245_CR59) 2022; 40 Z Fan (7245_CR17) 2022; 51 KT Baldwin (7245_CR48) 2021; 109 Y Zhou (7245_CR67) 2020; 11 JR Moffitt (7245_CR7) 2018; 362 VA Traag (7245_CR36) 2019; 9 Z Cang (7245_CR12) 2020; 11 B Gong (7245_CR28) 2021; 22 JD Welch (7245_CR13) 2019; 177 W Xiao (7245_CR8) 2018; 361 7245_CR46 SS Bahreiny (7245_CR51) 2024; 31 AR Wu (7245_CR4) 2014; 11 X Han (7245_CR62) 2018; 172 7245_CR42 B Tan (7245_CR49) 2014; 391 S Jin (7245_CR50) 2024; 10 A Joglekar (7245_CR70) 2021; 12 Y Takei (7245_CR61) 2021; 590 7245_CR1 A Zeisel (7245_CR35) 2015; 347 RD Hodge (7245_CR71) 2019; 573 ES Lein (7245_CR43) 2007; 445 NS Sherafat (7245_CR52) 2025; 25 G Zou (7245_CR31) 2025; 53 7245_CR38 7245_CR37 7245_CR34 7245_CR33 H Li (7245_CR40) 2022; 23 C-HL Eng (7245_CR65) 2019; 568 X Wang (7245_CR69) 2018; 361 MC Moh (7245_CR47) 2005; 42 X Li (7245_CR32) 2024; 25
References_xml	– volume: 9 start-page: 5233 year: 2019 ident: 7245_CR36 publication-title: Sci Rep doi: 10.1038/s41598-019-41695-z – ident: 7245_CR42 doi: 10.1038/s41586-021-03705-x – ident: 7245_CR6 – volume: 19 start-page: 662 year: 2022 ident: 7245_CR68 publication-title: Nat Methods doi: 10.1038/s41592-022-01480-9 – volume: 40 start-page: 121 year: 2022 ident: 7245_CR30 publication-title: Nat Biotechnol doi: 10.1038/s41587-021-01001-7 – volume: 25 start-page: bbae571 year: 2024 ident: 7245_CR32 publication-title: Briefings Bioinf doi: 10.1093/bib/bbae571 – volume: 31 start-page: 2957 year: 2024 ident: 7245_CR51 publication-title: Reprod Sci doi: 10.1007/s43032-024-01676-8 – volume: 445 start-page: 168 year: 2007 ident: 7245_CR43 publication-title: Nature doi: 10.1038/nature05453 – volume: 11 start-page: 6322 year: 2020 ident: 7245_CR67 publication-title: Nat Commun doi: 10.1038/s41467-020-20059-6 – volume: 11 start-page: 2084 year: 2020 ident: 7245_CR12 publication-title: Nat Commun doi: 10.1038/s41467-020-15968-5 – volume: 347 start-page: 1138 year: 2015 ident: 7245_CR35 publication-title: Science doi: 10.1126/science.aaa1934 – ident: 7245_CR37 doi: 10.1038/s41467-022-33758-z – volume: 568 start-page: 235 year: 2019 ident: 7245_CR65 publication-title: Nature doi: 10.1038/s41586-019-1049-y – ident: 7245_CR55 – volume: 177 start-page: 1873 year: 2019 ident: 7245_CR13 publication-title: Cell doi: 10.1016/j.cell.2019.05.006 – ident: 7245_CR2 doi: 10.1186/s40364-025-00738-6 – ident: 7245_CR29 – volume: 52 start-page: e52 year: 2024 ident: 7245_CR41 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkae409 – volume: 361 start-page: eaat5691 year: 2018 ident: 7245_CR69 publication-title: Science doi: 10.1126/science.aat5691 – volume: 111 start-page: 2675 year: 2023 ident: 7245_CR57 publication-title: Neuron doi: 10.1016/j.neuron.2023.05.032 – volume: 92 start-page: 342 year: 2016 ident: 7245_CR63 publication-title: Neuron doi: 10.1016/j.neuron.2016.10.001 – volume: 53 start-page: gkaf158 year: 2025 ident: 7245_CR31 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkaf158 – ident: 7245_CR21 – volume: 42 start-page: 833 year: 2005 ident: 7245_CR47 publication-title: J Hepatol doi: 10.1016/j.jhep.2005.01.025 – volume: 12 start-page: 463 year: 2021 ident: 7245_CR70 publication-title: Nat Commun doi: 10.1038/s41467-020-20343-5 – volume: 22 start-page: 351 year: 2021 ident: 7245_CR28 publication-title: Genome Biol doi: 10.1186/s13059-021-02556-z – ident: 7245_CR15 doi: 10.1007/978-3-319-20828-2 – volume: 573 start-page: 61 year: 2019 ident: 7245_CR71 publication-title: Nature doi: 10.1038/s41586-019-1506-7 – volume: 579 start-page: 1 year: 2020 ident: 7245_CR18 publication-title: Nature – ident: 7245_CR66 doi: 10.1073/pnas.1912459116 – ident: 7245_CR1 doi: 10.1007/s00277-025-06387-x – ident: 7245_CR56 – volume: 40 start-page: 74 year: 2022 ident: 7245_CR60 publication-title: Nat Biotechnol doi: 10.1038/s41587-021-01006-2 – volume: 590 start-page: 344 year: 2021 ident: 7245_CR61 publication-title: Nature doi: 10.1038/s41586-020-03126-2 – volume: 19 start-page: 41 year: 2022 ident: 7245_CR39 publication-title: Nat Methods doi: 10.1038/s41592-021-01336-8 – ident: 7245_CR11 doi: 10.1038/s41587-022-01448-2 – ident: 7245_CR16 doi: 10.1038/s41592-021-01264-7 – volume: 391 start-page: 95 year: 2014 ident: 7245_CR49 publication-title: Mol Cellular Biochem doi: 10.1007/s11010-014-1991-9 – ident: 7245_CR22 doi: 10.1101/2021.04.16.440115 – ident: 7245_CR58 doi: 10.1101/576827 – volume: 40 start-page: 517 year: 2022 ident: 7245_CR59 publication-title: Nat Biotechnol doi: 10.1038/s41587-021-00830-w – volume: 172 start-page: 1091 year: 2018 ident: 7245_CR62 publication-title: Cell doi: 10.1016/j.cell.2018.02.001 – volume: 362 start-page: 792 year: 2018 ident: 7245_CR7 publication-title: Science doi: 10.1126/science.aau5324 – volume: 25 start-page: 238 year: 2025 ident: 7245_CR52 publication-title: Clin Exp Med doi: 10.1007/s10238-025-01751-7 – ident: 7245_CR24 – volume: 109 start-page: 2427 year: 2021 ident: 7245_CR48 publication-title: Neuron doi: 10.1016/j.neuron.2021.05.025 – ident: 7245_CR19 doi: 10.1101/718395 – volume: 19 start-page: 1076 year: 2022 ident: 7245_CR44 publication-title: Nat Methods doi: 10.1038/s41592-022-01575-3 – volume: 16 start-page: 84 year: 2024 ident: 7245_CR3 publication-title: Iran J Blood And Cancer doi: 10.61186/ijbc.16.2.84 – volume: 23 start-page: 460 year: 2022 ident: 7245_CR40 publication-title: BMC Bioinf doi: 10.1186/s12859-022-05003-3 – ident: 7245_CR38 doi: 10.1186/s13059-021-02565-y – ident: 7245_CR53 – volume: 20 start-page: 218 year: 2023 ident: 7245_CR54 publication-title: Nat Methods doi: 10.1038/s41592-022-01728-4 – volume: 16 start-page: 4177 year: 2021 ident: 7245_CR14 publication-title: Nat Protoc doi: 10.1038/s41596-021-00573-7 – ident: 7245_CR27 – ident: 7245_CR34 – ident: 7245_CR46 doi: 10.1186/1750-1326-6-60 – ident: 7245_CR5 – ident: 7245_CR10 doi: 10.1101/2021.12.05.471303 – ident: 7245_CR64 doi: 10.1101/2020.08.27.268730 – ident: 7245_CR9 – volume: 361 start-page: eaat5691 year: 2018 ident: 7245_CR8 publication-title: Science doi: 10.1126/science.aat5691 – volume: 40 start-page: 1 year: 2009 ident: 7245_CR45 publication-title: Mol Cell Neurosci doi: 10.1016/j.mcn.2008.06.004 – volume: 10 start-page: eadq3350 year: 2024 ident: 7245_CR50 publication-title: Sci Adv doi: 10.1126/sciadv.adq3350 – volume: 11 start-page: 41 year: 2014 ident: 7245_CR4 publication-title: Nat Methods doi: 10.1038/nmeth.2694 – ident: 7245_CR33 – ident: 7245_CR26 – volume: 177 start-page: 1888 year: 2019 ident: 7245_CR20 publication-title: Cell doi: 10.1016/j.cell.2019.05.031 – ident: 7245_CR25 doi: 10.1038/s41592-018-0229-2 – volume: 51 start-page: D1138 year: 2022 ident: 7245_CR17 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkac889 – ident: 7245_CR23 doi: 10.1038/s41587-024-02193-4
SSID	ssj0024549
Score	2.440815
Snippet	Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both... Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both... The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding of both tissue... Abstract Background The integration of single-cell RNA sequencing (scRNA-seq) and high-resolution spatial transcriptomics (ST) could improve our understanding...
SourceID	doaj proquest gale pubmed crossref springer
SourceType	Open Website Aggregation Database Index Database Publisher
StartPage	1188
SubjectTerms	Anopheles Attention mechanism Biomedical and Life Sciences Biomedicine Cancer microenvironment Conditional variational autoencoder (CVAE) Gene imputation Gene mutations Genes Genetic research Genetic transcription Genomics Health aspects Identification and classification Medicine/Public Health Methods Neural networks Neurons RNA sequencing Single-cell RNA sequencing Spatial transcriptomics Technology application
SummonAdditionalLinks	– databaseName: SpringerLink Contemporary (1997 - Present) dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9wwEB5RiioutNACaaFyJaQe2ojE8dre3igCcSlCLSBulmM7iAMblOz20j_PjJNsWYoqtZdoFTvJrD2Pb2zPDMAe5dziusxSSieWCp-JdJyFPPWuKh0tuyknYrEJdXqqr67GZ31QWDucdh-2JKOmjmKt5X6LlgmFmsqv4vsFXp_BczR3msTx-4_L3xn20OUZwmOefG7BBMVM_X_q4wcG6dEOaTQ8xy__j-RXsNYDTXbQccY6LIXJBrz41m-lv4ZfVIw4HF5-YZHK9Lb2EZIzvF7HIwKsiXXqmz5Sk9UVo2V-Rqu2LbuJqxH4o6Uz2fgl5MRAd2fd5j5DNDxvm5JFjPqJgqDbN3BxfHR-eJL2lRhSJ5SapoVwBS9croOwIWguHPo91nI9KmUppUW3zfOAaE1IP8rywIP2COVGiAa814ghN2F5Uk_CNrASVYYqg8a-6BlWWWmlKlxVKHTUK6-LBD4Nk2PuuoQbJjoqWppuPA2Op4njabIEvtL8zXtSsux4o26uTS97xvJSBpsLX1ktrHNIdRBeSkqNr3WFn_xIs29IpHE8nO0jE5BgSo5lDjTCPCVVNkpgZ6EniqJbaP4w8I-hJjq_Ngn1rDUIkuVYIfkqga2OseY0izyXCApkAp8HLjK9Imn_8tff_lv3d7DKiRHR7PLxDixPm1nYhRX3c3rTNu-jBN0DJVAWog priority: 102 providerName: Springer Nature
Title	SpateCV: cross-modality alignment regularization of cell types improves spatial gene imputation for spatial transcriptomics
URI	https://link.springer.com/article/10.1186/s12967-025-07245-0 https://www.ncbi.nlm.nih.gov/pubmed/41162996 https://www.proquest.com/docview/3266971297 https://doaj.org/article/a2b6ea14dfa84acc85be4d66915588f3
Volume	23
WOSCitedRecordID	wos001605844500005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVADU databaseName: BioMedCentral customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: RBZ dateStart: 20030101 isFulltext: true titleUrlDefault: https://www.biomedcentral.com/search/ providerName: BioMedCentral – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: DOA dateStart: 20030101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: M~E dateStart: 20030101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: 7X7 dateStart: 20090101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: BENPR dateStart: 20090101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: PIMPY dateStart: 20090101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1479-5876 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024549 issn: 1479-5876 databaseCode: RSV dateStart: 20030601 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3dT9swED8NNqG9TNuALRurjDSJB4hIHNd29wYINB6oKrah8mQ5toN4WIualhf-ee6cpKJD2l72YiW2JZ99Z9-dP34H8JUwt7gus5TgxFLhM5EOspCn3lWlo2035UQMNqGGQz0eD0ZPQn3RnbAGHrgZuEPLSxlsLnxltbDO6X4ZhJeScM21riLOJ1o9nTPVoeyh29M9kdHysEathgsChW5F2gSmK2ooovU_X5OfKKU_Tkmj8jl7C29aq5EdNdS-gxdh8h42Ltpz8U14oMjC4eTqG4vNpb-nPtrXDNObeN7PZjHo_Kx9dsmmFaM9e0ZbsDW7jVsL-FHTBWtsCcUqUO6iOalnaNouy-ak3uJiQy-a6y34dXb68-R72oZVSJ1Qap4WwhW8cLkOwoaguXDoxFjLcWRlKaVFH8zzgKaXkL6f5YEH7dEu66Nq916jQbgN65PpJHwEVuL8V2XQWBfdvCorrVSFqwqFXnfldZHAfjfK5q5BzzDR69DSNDwxyBMTeWKyBI6JEcuahHwdM1AeTCsP5l_ykMAesdHQ_MTxcLZ9ZoAEE9KVOdJosympsn4COys1cV65leLdThAMFdFltEmYLmqDFq8cKCRfJfChkZAlzSLPJWp4mcBBJzKmXRXqv3T90__o-md4zUnEUbPywQ6sz2eL8AVeufv5bT3rwZoaq5jqHrw8Ph2OLntx0uDf6PxidI1_lz-uHgE1LRmB
linkProvider	Directory of Open Access Journals
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB6VgqAXnoWGFjASEgcakThe28utraiKaFeoLVVvlmM7VQ9sULLLhT_PjJMsXYoqwSVaxU4ya8_jG3tmDPCGam5xXWYplRNLhc9EOs5CnnpXlY6W3ZQT8bAJNZno8_Pxlz4prB2i3Yctyaipo1hr-b5Fy4RCTcev4vsFXm_BbYEWiwL5jk_OflfYQ5dnSI_563NLJihW6r-uj68YpD92SKPh2X_wfyQ_hPs90GQ7HWc8gpUwfQx3j_qt9Cfwkw4jDntnH1ikMv1W-wjJGV4vYogAa-I59U2fqcnqitEyP6NV25ZdxtUI_NFSTDZ-CTkx0N15t7nPEA0v2mZkEaN-oiTodh2-7n883TtI-5MYUieUmqWFcAUvXK6DsCFoLhz6PdZyPSplKaVFt83zgGhNSD_K8sCD9gjlRogGvNeIIZ_C6rSehg1gJaoMVQaNfdEzrLLSSlW4qlDoqFdeFwm8GybHfO8KbpjoqGhpuvE0OJ4mjqfJEtil-Vv0pGLZ8UbdXJhe9ozlpQw2F76yWljnkOogvJRUGl_rCj_5lmbfkEjjeDjbZyYgwVQcy-xohHlKqmyUwNZSTxRFt9T8euAfQ00UvzYN9bw1CJLlWCH5KoFnHWMtaBZ5LhEUyAS2By4yvSJpb_jrz_-t-yu4d3B6dGgOP00-b8IaJ6ZEE8zHW7A6a-bhBdxxP2aXbfMyStMvOOQZhg
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3Nb9UwDLdgoInL-GaFAUFC4gDV2jQvyeM2Bk8g4GkSMO0WpUk67UA7tX1c-Oex0_axBwgJcamqJFXcxI5_TmIb4CnF3OK6zFIKJ5YKn4l0noU89a4qHW27KSdisgm1XOqTk_nRBS_-eNt9OpIcfBooSlPd75_7ahBxLfc71FIo4JSKFfsS-LwMVwQlDSJ7_dPxz2h7aP5MrjJ__G5DHcWo_b-vzReU0y-npVEJLa7_P_k3YGcEoOxg4JibcCnUt2D743jEfhu-U5LicHj8kkWK06-Nj1Cd4fM0Xh1gbcxf344enKypGG3_M9rN7dhZ3KXAl47uamNPyKGBSlfDoT9DlLyu60lTxnWLnKO7O_Bl8ebz4dt0zNCQOqFUnxbCFbxwuQ7ChqC5cGgPWcv1rJSllBbNOc8Dojgh_SzLAw_aI8SbIUrwXiO2vAtbdVOHXWAlLiWqDBrbosVYZaWVqnBVodCAr7wuEng-TZQ5HwJxmGjAaGmG8TQ4niaOp8kSeEVzuW5JQbRjQdOemlEmjeWlDDYXvrJaWOeQ6iC8lBQyX-sKu3xGnGBI1HE8nB09FpBgCpplDjTCPyVVNktgb6MliqjbqH4y8ZKhKrrXVodm1RkEz3KukHyVwL2BydY0izyXCBZkAi8mjjLjAtP95dfv_1vzx7B99HphPrxbvn8A1zjxJGpmPt-Drb5dhYdw1X3rz7r2URSsH2byImo
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=SpateCV%3A+cross-modality+alignment+regularization+of+cell+types+improves+spatial+gene+imputation+for+spatial+transcriptomics&rft.jtitle=Journal+of+translational+medicine&rft.au=Jiaqi+Yuan&rft.au=Junhua+Yu&rft.au=Qianbei+Yi&rft.au=Zheng+Ye&rft.date=2025-10-29&rft.pub=BMC&rft.eissn=1479-5876&rft.volume=23&rft.issue=1&rft.spage=1&rft.epage=21&rft_id=info:doi/10.1186%2Fs12967-025-07245-0&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_a2b6ea14dfa84acc85be4d66915588f3
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1479-5876&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1479-5876&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1479-5876&client=summon