These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
209 related articles for article (PubMed ID: 38413725)
21. A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data. Zhang L; Liang S; Wan L Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38801701 [TBL] [Abstract][Full Text] [Related]
22. SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis. Aihara G; Clifton K; Chen M; Li Z; Atta L; Miller BF; Satija R; Hickey JW; Fan J Bioinformatics; 2024 Jul; 40(7):. PubMed ID: 38902953 [TBL] [Abstract][Full Text] [Related]
23. SMaSH: a scalable, general marker gene identification framework for single-cell RNA-sequencing. Nelson ME; Riva SG; Cvejic A BMC Bioinformatics; 2022 Aug; 23(1):328. PubMed ID: 35941549 [TBL] [Abstract][Full Text] [Related]
24. FICTURE: scalable segmentation-free analysis of submicron-resolution spatial transcriptomics. Si Y; Lee C; Hwang Y; Yun JH; Cheng W; Cho CS; Quiros M; Nusrat A; Zhang W; Jun G; Zöllner S; Lee JH; Kang HM Nat Methods; 2024 Oct; 21(10):1843-1854. PubMed ID: 39266749 [TBL] [Abstract][Full Text] [Related]
25. A Primer on Preprocessing, Visualization, Clustering, and Phenotyping of Barcode-Based Spatial Transcriptomics Data. Ospina O; Soupir A; Fridley BL Methods Mol Biol; 2023; 2629():115-140. PubMed ID: 36929076 [TBL] [Abstract][Full Text] [Related]
26. BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data. Fu X; Lin Y; Lin DM; Mechtersheimer D; Wang C; Ameen F; Ghazanfar S; Patrick E; Kim J; Yang JYH Nat Commun; 2024 Jan; 15(1):509. PubMed ID: 38218939 [TBL] [Abstract][Full Text] [Related]
27. DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data. Mrukwa G; Polanska J BMC Bioinformatics; 2022 Dec; 23(1):538. PubMed ID: 36503372 [TBL] [Abstract][Full Text] [Related]
28. Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods. Charitakis N; Salim A; Piers AT; Watt KI; Porrello ER; Elliott DA; Ramialison M Genome Biol; 2023 Sep; 24(1):209. PubMed ID: 37723583 [TBL] [Abstract][Full Text] [Related]
29. spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics. Zhang C; Liu L; Zhang Y; Li M; Fang S; Kang Q; Chen A; Xu X; Zhang Y; Li Y Gigascience; 2024 Jan; 13():. PubMed ID: 39028588 [TBL] [Abstract][Full Text] [Related]
30. SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes. Yang Y; Shi X; Liu W; Zhou Q; Chan Lau M; Chun Tatt Lim J; Sun L; Ng CCY; Yeong J; Liu J Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34849574 [TBL] [Abstract][Full Text] [Related]
31. Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution. Li B; Zhang W; Guo C; Xu H; Li L; Fang M; Hu Y; Zhang X; Yao X; Tang M; Liu K; Zhao X; Lin J; Cheng L; Chen F; Xue T; Qu K Nat Methods; 2022 Jun; 19(6):662-670. PubMed ID: 35577954 [TBL] [Abstract][Full Text] [Related]
32. Computational Approaches and Challenges in Spatial Transcriptomics. Fang S; Chen B; Zhang Y; Sun H; Liu L; Liu S; Li Y; Xu X Genomics Proteomics Bioinformatics; 2023 Feb; 21(1):24-47. PubMed ID: 36252814 [TBL] [Abstract][Full Text] [Related]
33. Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion. Li Z; Song T; Yong J; Kuang R PLoS Comput Biol; 2021 Apr; 17(4):e1008218. PubMed ID: 33826608 [TBL] [Abstract][Full Text] [Related]
34. SpaNCMG: improving spatial domains identification of spatial transcriptomics using neighborhood-complementary mixed-view graph convolutional network. Si Z; Li H; Shang W; Zhao Y; Kong L; Long C; Zuo Y; Feng Z Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38811360 [TBL] [Abstract][Full Text] [Related]
35. DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics. Rahimi A; Vale-Silva LA; Fälth Savitski M; Tanevski J; Saez-Rodriguez J Nat Commun; 2024 Jun; 15(1):4994. PubMed ID: 38862466 [TBL] [Abstract][Full Text] [Related]
36. Reference-based cell type matching of in situ image-based spatial transcriptomics data on primary visual cortex of mouse brain. Zhang Y; Miller JA; Park J; Lelieveldt BP; Long B; Abdelaal T; Aevermann BD; Biancalani T; Comiter C; Dzyubachyk O; Eggermont J; Langseth CM; Petukhov V; Scalia G; Vaishnav ED; Zhao Y; Lein ES; Scheuermann RH Sci Rep; 2023 Jun; 13(1):9567. PubMed ID: 37311768 [TBL] [Abstract][Full Text] [Related]
37. Scalable and model-free detection of spatial patterns and colocalization. Liu Q; Hsu CY; Shyr Y Genome Res; 2022 Sep; 32(9):1736-1745. PubMed ID: 36223499 [TBL] [Abstract][Full Text] [Related]
38. PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics. Liang Y; Shi G; Cai R; Yuan Y; Xie Z; Yu L; Huang Y; Shi Q; Wang L; Li J; Tang Z Nat Commun; 2024 Jan; 15(1):600. PubMed ID: 38238417 [TBL] [Abstract][Full Text] [Related]
39. TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses. Sun ED; Ma R; Navarro Negredo P; Brunet A; Zou J Nat Methods; 2024 Mar; 21(3):444-454. PubMed ID: 38347138 [TBL] [Abstract][Full Text] [Related]
40. Evaluating spatially variable gene detection methods for spatial transcriptomics data. Chen C; Kim HJ; Yang P Genome Biol; 2024 Jan; 25(1):18. PubMed ID: 38225676 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]