Difference between revisions of "Journal Club"
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|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
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[https://doi.org/10.1038/s43018-022-00433-7 Single-cell meta-analyses reveal responses of tumor-reactive CXCL13+ T cells to immune-checkpoint blockade] | [https://doi.org/10.1038/s43018-022-00433-7 Single-cell meta-analyses reveal responses of tumor-reactive CXCL13+ T cells to immune-checkpoint blockade] | ||
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[https://doi.org/10.1038/s41587-022-01342-x Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression] | [https://doi.org/10.1038/s41587-022-01342-x Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression] | ||
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[https://doi.org/10.1038/s41587-022-01288-0 DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data] | [https://doi.org/10.1038/s41587-022-01288-0 DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data] | ||
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[https://doi.org/10.1016/j.xgen.2022.100166 Functional inference of gene regulation using single-cell multi-omics] | [https://doi.org/10.1016/j.xgen.2022.100166 Functional inference of gene regulation using single-cell multi-omics] | ||
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|style="padding:.4em;"|23-17 | |style="padding:.4em;"|23-17 | ||
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[https://doi.org/10.1016/j.patter.2022.100651 Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships] | [https://doi.org/10.1016/j.patter.2022.100651 Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships] | ||
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[https://doi.org/10.1016/j.ccell.2022.10.008 High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer] | [https://doi.org/10.1016/j.ccell.2022.10.008 High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer] | ||
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[https://doi.org/10.1186/s13059-022-02828-2 Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment] | [https://doi.org/10.1186/s13059-022-02828-2 Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment] | ||
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[https://doi.org/10.1038/s41467-022-32838-4 Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma] | [https://doi.org/10.1038/s41467-022-32838-4 Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma] | ||
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[https://doi.org/10.1038/s43018-021-00292-8 Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer] | [https://doi.org/10.1038/s43018-021-00292-8 Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer] | ||
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[https://doi.org/10.1016/j.cell.2022.11.028 Integrative single-cell analysis of cardiogenesis indentifies developmental trajectories and non-conding mutations in congenital heart disease] | [https://doi.org/10.1016/j.cell.2022.11.028 Integrative single-cell analysis of cardiogenesis indentifies developmental trajectories and non-conding mutations in congenital heart disease] | ||
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[https://doi.org/10.1101/2022.12.20.521311 Supervised discovery of interpretable gene programs from single-cell data] | [https://doi.org/10.1101/2022.12.20.521311 Supervised discovery of interpretable gene programs from single-cell data] | ||
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[https://doi.org/10.1038/s41586-022-05435-0 Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer] | [https://doi.org/10.1038/s41586-022-05435-0 Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer] | ||
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|style="padding:.4em;" rowspan=1|Microbiome | |style="padding:.4em;" rowspan=1|Microbiome | ||
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[https://doi.org/10.1016/j.chom.2020.03.005 Structure of the Mucosal and Stool Microbiome in Lynch Syndrome] | [https://doi.org/10.1016/j.chom.2020.03.005 Structure of the Mucosal and Stool Microbiome in Lynch Syndrome] | ||
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[https://doi.org/10.1038/s41586-019-1237-9 Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases] | [https://doi.org/10.1038/s41586-019-1237-9 Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases] | ||
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[https://doi.org/10.1016/j.jare.2022.03.007 Roles of oral microbiota and oral-gut microbial transmission in hypertension] | [https://doi.org/10.1016/j.jare.2022.03.007 Roles of oral microbiota and oral-gut microbial transmission in hypertension] | ||
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[https://doi.org/10.1038/s41467-022-33397-4 Deciphering microbial gene function using natural language processing] | [https://doi.org/10.1038/s41467-022-33397-4 Deciphering microbial gene function using natural language processing] | ||
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[https://doi.org/10.1186/s40168-022-01435-4 Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi‑omic analyses] | [https://doi.org/10.1186/s40168-022-01435-4 Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi‑omic analyses] | ||
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[https://doi.org/10.1016/j.immuni.2022.08.016 The CD4+ T cell response to a commensal-derived epitope transitions from a tolerant to an inflammatory state in Crohn’s disease] | [https://doi.org/10.1016/j.immuni.2022.08.016 The CD4+ T cell response to a commensal-derived epitope transitions from a tolerant to an inflammatory state in Crohn’s disease] | ||
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[https://doi.org/10.1038/s41591-018-0203-7 Antigen discovery and specification of immunodominance hierarchies for MHCIIrestricted epitopes] | [https://doi.org/10.1038/s41591-018-0203-7 Antigen discovery and specification of immunodominance hierarchies for MHCIIrestricted epitopes] | ||
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[https://doi.org/10.1101/2022.10.11.511790 Single Cell Transcriptomics Reveals the Hidden Microbiomes of Human Tissues] | [https://doi.org/10.1101/2022.10.11.511790 Single Cell Transcriptomics Reveals the Hidden Microbiomes of Human Tissues] | ||
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[https://doi.org/10.1038/s41564-017-0096-0 Stability of the human faecal microbiome in a cohort of adult men] | [https://doi.org/10.1038/s41564-017-0096-0 Stability of the human faecal microbiome in a cohort of adult men] | ||
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Revision as of 01:04, 3 April 2023
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2023/07/05 | Single-cell | 23-21 | G Koh | |
2023/06/28 | Single-cell | 23-20 | JW Yu |
Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression |
2023/06/21 | Single-cell | 23-19 | JH Cha |
DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data |
2023/06/14 | Single-cell | 23-18 | SB Baek |
Functional inference of gene regulation using single-cell multi-omics |
2023/06/07 | Single-cell | 23-17 | EJ Sung | |
2023/05/31 | Single-cell | 23-16 | IS Choi | |
2023/05/24 | Single-cell | 23-15 | G Koh | |
2023/05/17 | Single-cell | 23-14 | JW Yu |
Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma |
2023/05/10 | Single-cell | 23-13 | JH Cha | |
2023/05/03 | Single-cell | 23-12 | SB Baek | |
2023/04/26 | Single-cell | 23-11 | EJ Sung |
Supervised discovery of interpretable gene programs from single-cell data |
2023/04/19 | Single-cell | 23-10 | IS Choi |
Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer |
2023/04/12 | 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 |