Difference between revisions of "Journal Club"
(16 intermediate revisions by 2 users not shown) | |||
Line 55: | Line 55: | ||
|style="padding:.4em;"|YK Jung | |style="padding:.4em;"|YK Jung | ||
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https:// | + | [https://www.sciencedirect.com/science/article/pii/S1534580722002519?via%3Dihub The single-cell stereo-seq reveals region-specific cell subtypes and transcriptome profiling in Arabidopsis leaves] |
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/06/11 | |style="padding:.4em;" rowspan=1|2024/06/11 | ||
Line 104: | Line 104: | ||
|style="padding:.4em;"|YH Lee | |style="padding:.4em;"|YH Lee | ||
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https://doi.org/10.1038/ | + | [https://doi.org/10.1038/s41564-023-01462-3 Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection] |
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/05/28 | |style="padding:.4em;" rowspan=1|2024/05/28 | ||
Line 172: | Line 172: | ||
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|24-9 | |style="padding:.4em;"|24-9 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|Q Zhen |
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
[https://doi.org/10.1021/acscentsci.3c01169 Single-Cell Analysis Reveals Cxcl14+ Fibroblast Accumulation in Regenerating Diabetic Wounds Treated by Hydrogel-Delivering Carbon Monoxide] | [https://doi.org/10.1021/acscentsci.3c01169 Single-Cell Analysis Reveals Cxcl14+ Fibroblast Accumulation in Regenerating Diabetic Wounds Treated by Hydrogel-Delivering Carbon Monoxide] | ||
Line 243: | Line 243: | ||
!scope="col" style="padding:.4em" | Presenter | !scope="col" style="padding:.4em" | Presenter | ||
!scope="col" style="padding:.4em" | Paper title | !scope="col" style="padding:.4em" | Paper title | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/20 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|HB Lee | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.immuni.2024.02.007 CD4+ T cell activation distinguishes response to anti-PD-L1+anti-CTLA4 therapy from anti-PD-L1 monotherapy] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/20 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|YL Jung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.ccell.2023.12.012 Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/20 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2023.11.037 A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/13 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41467-024-48310-4 Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/06 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41592-024-02175-z SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/30 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-20 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.06.04.597354 Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation Model] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/23 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-19 | ||
+ | |style="padding:.4em;"|HB Lee | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.ccell.2023.12.013 Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lungcancer] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/16 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-18 | ||
+ | |style="padding:.4em;"|YL Jung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.xgen.2023.100473 Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/09 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-17 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.06.16.599201 node2vec2rank: Large Scale and Stable Graph Differential Analysis via Multi-Layer Node Embeddings and Ranking] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/02 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-16 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41592-024-02305-7 Large-scale foundation model on single-cell transcriptomics] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/26 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-15 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.xgen.2024.100553 Unified cross-modality integration and analysis of T cell receptors and T cell transcriptomes by low-resource-aware representation learning] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/19 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-14 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2023.07.18.549602 Contextual AI models for single-cell protein biology] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/12 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-13 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.04.15.589472 Nicheformer: a foundation model for single-cell and spatial omics] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/05 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-12 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2023.05.29.542705 Large Scale Foundation Model on Single-cell Transcriptomics] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/28 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-11 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41592-024-02201-0 scGPT: toward building a foundation modelfor single-cell multi-omics using generative AI] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/21 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-10 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41586-023-06139-9 Transfer learning enables predictions in network biology] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/07 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-9 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1158/0008-5472.CAN-23-2650 The Web-Based Portal SpatialTME Integrates Histological Images with Single-Cell and Spatial Transcriptomics to Explore the Tumor Microenvironment] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/05/17 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|24-8 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41592-023-02117-1 SEVtras delineates small extracellular vesicles at droplet resolution from single-cell transcriptomes] | ||
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/05/10 | |style="padding:.4em;" rowspan=1|2024/05/10 | ||
Line 253: | Line 379: | ||
|style="padding:.4em;" rowspan=1|2024/05/03 | |style="padding:.4em;" rowspan=1|2024/05/03 | ||
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
− | |style="padding:.4em;"|24- | + | |style="padding:.4em;"|24-5 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|EJ Sung |
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https://doi.org/10.1038/ | + | [https://doi.org/10.1038/s41467-023-44206-x Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity] |
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/04/26 | |style="padding:.4em;" rowspan=1|2024/04/26 | ||
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
− | |style="padding:.4em;"|24- | + | |style="padding:.4em;"|24-6 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JH Cha |
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https://doi.org/10.1038/ | + | [https://doi.org/10.1038/s41587-023-01734-7 Dandelion uses the single-cell adaptive immune receptor repertoire to explore lymphocyte developmental origins] |
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/04/05 | |style="padding:.4em;" rowspan=1|2024/04/05 | ||
Line 303: | Line 429: | ||
!scope="col" style="padding:.4em" | Presenter | !scope="col" style="padding:.4em" | Presenter | ||
!scope="col" style="padding:.4em" | Paper title | !scope="col" style="padding:.4em" | Paper title | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/21 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|NY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.chom.2024.03.005 A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/14 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|YR Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41586-024-07487-w Accurate structure prediction of biomolecular interactions with AlphaFold 3] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/14 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|JY kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41591-024-02963-2 Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/07 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|WJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1186/s40168-023-01737-1 Gut microbiome-metabolome interactions predict host condition] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/07 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|G Koh | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41587-023-01917-2 Protein remote homology detection and structural alignment using deep learning] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/31 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|SH Ahn | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41564-024-01751-5 A multi-kingdom collection of 33,804 reference genomes for the human vaginal microbiome] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/31 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|HJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2023.12.11.571168 Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/24 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|JY Ma | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.06.04.596112 Compositional Differential Abundance Testing: Defining and Finding a New Type of Health-Microbiome Associations] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/24 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.05.013 Discovery of antimicrobial peptides in the global microbiome with machine learning] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/17 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|NY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.05.029 Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/17 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|YR Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41586-024-07336-w Paternal microbiome perturbations impact offspring fitness] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/10 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|JY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.crmeth.2024.100775 Interactions-based classification of a single microbial sample] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/10 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-23 | ||
+ | |style="padding:.4em;"|NY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.04.10.588779 Accurate estimation of intraspecificmicrobial gene content variation inmetagenomic data with MIDAS v3 andStrainPGC] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/03 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-29 | ||
+ | |style="padding:.4em;"|WJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.03.021 A pan-cancer analysis of the microbiome inmetastatic cancer] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/07/03 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-28 | ||
+ | |style="padding:.4em;"|G Koh | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.chom.2024.03.002 A specific enterotype derived from gut microbiomeof older individuals enables favorable responses toimmune checkpoint blockade therapy] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/26 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-27 | ||
+ | |style="padding:.4em;"|SH Ahn | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.chom.2024.02.010 Stratification of Fusobacterium nucleatum by localhealth status in the oral cavity defines its subspeciesdisease association] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/26 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-26 | ||
+ | |style="padding:.4em;"|HJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1080/19490976.2024.2309684 A universe of human gut-derived bacterialprophages: unveiling the hidden viral players inintestinal microecology] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/19 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-25 | ||
+ | |style="padding:.4em;"|JY Ma | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41388-024-02974-w Robustness of cancer microbiome signals over a broad range of methodological variation] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/19 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-24 | ||
+ | |style="padding:.4em;"|JY Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41586-024-07182-w A distinct Fusobacterium nucleatum clade dominates the colorectal cancer niche] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/05 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-22 | ||
+ | |style="padding:.4em;"|YR Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.01.039 A cryptic plasmid is among the most numerous genetic elements in the human gut] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/06/05 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-21 | ||
+ | |style="padding:.4em;"|JY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.03.014 Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/05/29 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-20 | ||
+ | |style="padding:.4em;"|WJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2024.03.18.584290 Fecal microbial load is a major determinant of gut microbiome variation and aconfounder for disease associations] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/05/29 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-19 | ||
+ | |style="padding:.4em;"|G Koh | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41586-024-07162-0 A host-microbiota interactome reveals extensive transkingdom connectivity] | ||
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/05/22 | |style="padding:.4em;" rowspan=1|2024/05/22 | ||
Line 316: | Line 603: | ||
|style="padding:.4em;"|HJ Kim | |style="padding:.4em;"|HJ Kim | ||
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https://doi.org/10.1038/ | + | [https://doi.org/10.1038/s41467-024-45793-z A metagenomic catalog of the early-life human gut virome] |
|- | |- | ||
|style="padding:.4em;" rowspan=1|2024/05/08 | |style="padding:.4em;" rowspan=1|2024/05/08 |
Revision as of 13:56, 30 June 2024
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2024/06/18 | Single-cell | 24-32 | EB Hong |
Spatial transcriptomics reveal neuron–astrocyte synergy in long-term memory |
2024/06/18 | Single-cell | 24-31 | JJ Heo |
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses |
2024/06/18 | Single-cell | 24-30 | SM Han |
Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution |
2024/06/18 | Single-cell | 24-29 | HJ Choi | |
2024/06/11 | Single-cell | 24-28 | SA Choi | |
2024/06/11 | Single-cell | 24-27 | HJ Cha |
Cell-type-specific responses to fungal infection in plants revealed by single-cell transcriptomics |
2024/06/11 | Single-cell | 24-26 | YK Jung | |
2024/06/11 | Single-cell | 24-25 | HJ Lee | |
2024/06/04 | Single-cell | 24-24 | HK Lee |
Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas |
2024/06/04 | Single-cell | 24-23 | JI Lee |
Multimodal spatiotemporal phenotyping of human retinal organoid development |
2024/06/04 | Single-cell | 24-22 | JH Lee | |
2024/06/04 | Single-cell | 24-21 | JH Lee |
A single-cell analysis of the Arabidopsis vegetative shoot apex |
2024/05/28 | Single-cell | 24-20 | JH Lee |
Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq |
2024/05/28 | Single-cell | 24-19 | YH Lee | |
2024/05/28 | Single-cell | 24-18 | EB Yu | |
2024/05/28 | Single-cell | 24-17 | DY Won |
Spatial metatranscriptomics resolves host–bacteria–fungi interactomes |
2024/05/21 | Single-cell | 24-16 | SG Oh | |
2024/05/21 | Single-cell | 24-15 | SY Park | |
2024/05/21 | Single-cell | 24-14 | HS Moon | |
2024/05/21 | Single-cell | 24-13 | JH Nam |
Spatial cellular architecture predicts prognosis in glioblastoma |
2024/05/14 | Single-cell | 24-12 | HS Na | |
2024/05/14 | Single-cell | 24-11 | PK Kim |
Transcriptional adaptation of olfactory sensory neurons to GPCR identity and activity |
2024/05/14 | Single-cell | 24-10 | SH Kwon | |
2024/05/14 | Single-cell | 24-9 | Q Zhen | |
2024/05/07 | Single-cell | 24-8 | CR Leenaars | |
2024/05/07 | Single-cell | 24-7 | YR Kim | |
2024/05/07 | Single-cell | 24-6 | JY Kim |
Spatial transcriptomics landscape of lesions from non-communicable inflammatory skin diseases |
2024/05/07 | Single-cell | 24-5 | WJ Kim |
Neuregulin 4 suppresses NASH-HCC development by restraining tumor-prone liver microenvironment |
2024/04/23 | Single-cell | 24-4 | G Koh |
Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer’s disease |
2024/04/23 | Single-cell | 24-3 | SH Ahn | |
2024/04/23 | Single-cell | 24-2 | EJ Sung | |
2024/04/23 | Single-cell | 24-1 | HJ Kim |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2023/08/30 | Single-cell | 23-24 | JW Yu | |
2023/08/09 | Single-cell | 23-23 | IS Choi |
Major data analysis errors invalidate cancer microbiome findings |
2023/08/02 | Single-cell | 23-22 | EJ Sung | |
2023/07/26 | Single-cell | 23-21 | G Koh | |
2023/07/19 | Single-cell | 23-20 | JW Yu |
Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression |
2023/07/12 | Single-cell | 23-19 | JH Cha |
DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data |
2023/07/05 | Single-cell | 23-18 | SB Baek |
Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance |
2023/06/28 | Single-cell | 23-17 | EJ Sung | |
2023/06/21 | Single-cell | 23-16 | IS Choi | |
2023/06/14 | Single-cell | 23-15 | G Koh | |
2023/05/31 | Single-cell | 23-14 | JW Yu |
Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma |
2023/05/24 | Single-cell | 23-13 | JH Cha | |
2023/05/17 | Single-cell | 23-12 | SB Baek | |
2023/05/10 | Single-cell | 23-11 | EJ Sung |
Supervised discovery of interpretable gene programs from single-cell data |
2023/05/03 | Single-cell | 23-10 | IS Choi |
Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer |
2023/04/26 | Single-cell | 23-9 | G Koh | |
2023/03/22 | Single-cell | 23-8 | JW Yu |
MetaTiME: Meta-components of the Tumor Immune Microenvironment |
2023/03/08 | Single-cell | 23-7 | JH Cha | |
2023/02/21 | Single-cell | 23-6 | SB Baek | |
2023/02/14 | Single-cell | 23-5 | EJ Sung |
A T cell resilience model associated with response to immunotherapy in multiple tumor types |
2022/01/31 | Single-cell | 23-4 | IS Choi | |
2023/01/25 | Single-cell | 23-3 | G Koh | |
2023/01/17 | Single-cell | 23-2 | JW Yu |
Pan-cancer integrative histology-genomic analysis via multimodal deep learning |
2023/01/11 | Single-cell | 23-1 | JH Cha |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2021/11/23 | Single-cell | 21-39 | IS Choi | |
2021/11/16 | Single-cell | 21-38 | SB Back | |
2021/11/09 | Single-cell | 21-37 | JH Cha | |
2021/11/02 | Single-cell | 21-36 | SB Baek |
Functional Inference of Gene Regulation using Single-Cell Multi-Omics |
2021/10/26 | Single-cell | 21-35 | IS Choi | |
2021/10/19 | Single-cell | 21-34 | JH Cha | |
2021/10/05 | Single-cell | 21-33 | JH Cha |
Tumor and immune reprogramming during immunotherapy in advanced renal cell carcinoma |
2021/09/28 | Single-cell | 21-32 | SB Baek | |
2021/09/14 | Single-cell | 21-31 | IS Choi | |
2021/09/07 | Single-cell | 21-30 | JH Cha |
A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer |
2021/08/31 | Single-cell | 21-29 | IS Choi |
Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma |
2021/08/24 | Single-cell | 21-28 | SB Baek |
Interpreting type 1 diabetes risk with genetics and single-cell epigenomics |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2021/02/22 | Single-cell | 21-8 | IS Choi |
Functional CRISPR dissection of gene networks controlling human regulatory T cell identity |
21-7 | JH Cha |
Molecular Pathways of Colon Inflammation Induced by Cancer Immunotherapy | ||
2021/02/15 | Single-cell | 21-6 | SB Baek | |
21-5 | IS Choi |
Trajectory-based differential expression analysis for single-cell sequencing data | ||
2021/02/08 | Single-cell | 21-4 | SB Baek |
Genetic determinants of co-accessible chromatin regions in activated T cells across humans |
21-3 | JH Cha |
Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer | ||
2021/02/01 | Single-cell | 21-2 | JW Cho | |
21-1 | JW Cho |