131 related articles for article (PubMed ID: 38160299)
1. Enhancing Spatial Transcriptomics Analysis by Integrating Image-Aware Deep Learning Methods.
Song J; Lamstein J; Ramaswamy VG; Webb M; Zada G; Finkbeiner S; Craig DW
Pac Symp Biocomput; 2024; 29():450-463. PubMed ID: 38160299
[TBL] [Abstract][Full Text] [Related]
2. Computational solutions for spatial transcriptomics.
Kleino I; Frolovaitė P; Suomi T; Elo LL
Comput Struct Biotechnol J; 2022; 20():4870-4884. PubMed ID: 36147664
[TBL] [Abstract][Full Text] [Related]
3. Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning.
Laubscher E; Wang X; Razin N; Dougherty T; Xu RJ; Ombelets L; Pao E; Graf W; Moffitt JR; Yue Y; Van Valen D
Cell Syst; 2024 May; 15(5):475-482.e6. PubMed ID: 38754367
[TBL] [Abstract][Full Text] [Related]
4. Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis.
Azher ZL; Fatemi M; Lu Y; Srinivasan G; Diallo AB; Christensen BC; Salas LA; Kolling FW; Perreard L; Palisoul SM; Vaickus LJ; Levy JJ
Pac Symp Biocomput; 2024; 29():464-476. PubMed ID: 38160300
[TBL] [Abstract][Full Text] [Related]
5. THItoGene: a deep learning method for predicting spatial transcriptomics from histological images.
Jia Y; Liu J; Chen L; Zhao T; Wang Y
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38145948
[TBL] [Abstract][Full Text] [Related]
6. Single-cell level deconvolution, convolution, and clustering in spatial transcriptomics by aligning spot level transcriptome to nuclear morphology.
Zhu S; Kubota N; Wang S; Wang T; Xiao G; Hoshida Y
bioRxiv; 2023 Dec; ():. PubMed ID: 38187541
[TBL] [Abstract][Full Text] [Related]
7. Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images.
Bae S; Choi H; Lee DS
Nucleic Acids Res; 2021 Jun; 49(10):e55. PubMed ID: 33619564
[TBL] [Abstract][Full Text] [Related]
8. PAGE-Net: Interpretable and Integrative Deep Learning for Survival Analysis Using Histopathological Images and Genomic Data.
Hao J; Kosaraju SC; Tsaku NZ; Song DH; Kang M
Pac Symp Biocomput; 2020; 25():355-366. PubMed ID: 31797610
[TBL] [Abstract][Full Text] [Related]
9. Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding.
Li Y; Zhang J; Gao X; Zhang QC
Cell Syst; 2024 Jun; 15(6):578-592.e7. PubMed ID: 38823396
[TBL] [Abstract][Full Text] [Related]
10. Inferring spatial transcriptomics markers from whole slide images to characterize metastasis-related spatial heterogeneity of colorectal tumors: A pilot study.
Fatemi M; Feng E; Sharma C; Azher Z; Goel T; Ramwala O; Palisoul SM; Barney RE; Perreard L; Kolling FW; Salas LA; Christensen BC; Tsongalis GJ; Vaickus LJ; Levy JJ
J Pathol Inform; 2023; 14():100308. PubMed ID: 37114077
[TBL] [Abstract][Full Text] [Related]
11. The Overlooked Role of Specimen Preparation in Bolstering Deep Learning-Enhanced Spatial Transcriptomics Workflows.
Fatemi MY; Lu Y; Diallo AB; Srinivasan G; Azher ZL; Christensen BC; Salas LA; Tsongalis GJ; Palisoul SM; Perreard L; Kolling FW; Vaickus LJ; Levy JJ
medRxiv; 2023 Oct; ():. PubMed ID: 37873287
[TBL] [Abstract][Full Text] [Related]
12. Identifying spatial domain by adapting transcriptomics with histology through contrastive learning.
Zeng Y; Yin R; Luo M; Chen J; Pan Z; Lu Y; Yu W; Yang Y
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36781228
[TBL] [Abstract][Full Text] [Related]
13. Integrating spatial gene expression and breast tumour morphology via deep learning.
He B; Bergenstråhle L; Stenbeck L; Abid A; Andersson A; Borg Å; Maaskola J; Lundeberg J; Zou J
Nat Biomed Eng; 2020 Aug; 4(8):827-834. PubMed ID: 32572199
[TBL] [Abstract][Full Text] [Related]
14. Deep learning in spatially resolved transcriptfomics: a comprehensive technical view.
Zahedi R; Ghamsari R; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38483255
[TBL] [Abstract][Full Text] [Related]
15. Integrating multi-modal information to detect spatial domains of spatial transcriptomics by graph attention network.
Huo Y; Guo Y; Wang J; Xue H; Feng Y; Chen W; Li X
J Genet Genomics; 2023 Sep; 50(9):720-733. PubMed ID: 37356752
[TBL] [Abstract][Full Text] [Related]
16. A review on deep learning applications in highly multiplexed tissue imaging data analysis.
Zidane M; Makky A; Bruhns M; Rochwarger A; Babaei S; Claassen M; Schürch CM
Front Bioinform; 2023; 3():1159381. PubMed ID: 37564726
[TBL] [Abstract][Full Text] [Related]
17. Graph deep learning enabled spatial domains identification for spatial transcriptomics.
Liu T; Fang ZY; Li X; Zhang LN; Cao DS; Yin MZ
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37080761
[TBL] [Abstract][Full Text] [Related]
18. A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival.
Jaber MI; Song B; Taylor C; Vaske CJ; Benz SC; Rabizadeh S; Soon-Shiong P; Szeto CW
Breast Cancer Res; 2020 Jan; 22(1):12. PubMed ID: 31992350
[TBL] [Abstract][Full Text] [Related]
19. Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis.
Azher Z; Fatemi M; Lu Y; Srinivasan G; Diallo A; Christensen B; Salas L; Kolling F; Perreard L; Palisoul S; Vaickus L; Levy J
bioRxiv; 2023 Jul; ():. PubMed ID: 37577686
[TBL] [Abstract][Full Text] [Related]
20. Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity.
Fatemi MY; Lu Y; Sharma C; Feng E; Azher ZL; Diallo AB; Srinivasan G; Rosner GM; Pointer KB; Christensen BC; Salas LA; Tsongalis GJ; Palisoul SM; Perreard L; Kolling FW; Vaickus LJ; Levy JJ
medRxiv; 2023 Oct; ():. PubMed ID: 37873186
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
