Difference between revisions of "Journal Club"
From Bioinformatics Lab
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|style="padding:.4em;"|21-27 | |style="padding:.4em;"|21-27 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|HJ Kim |
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[https://www.sciencedirect.com/science/article/pii/S1931312820306193 Automated Prediction and Annotation of Small Open Reading Frames in Microbial Genomes] | [https://www.sciencedirect.com/science/article/pii/S1931312820306193 Automated Prediction and Annotation of Small Open Reading Frames in Microbial Genomes] | ||
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|style="padding:.4em;"|21-26 | |style="padding:.4em;"|21-26 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JY Ma |
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[https://www.sciencedirect.com/science/article/pii/S1931312820305734 Identification of Natural CRISPR Systems and Targets in the Human Microbiome] | [https://www.sciencedirect.com/science/article/pii/S1931312820305734 Identification of Natural CRISPR Systems and Targets in the Human Microbiome] | ||
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− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JK Yoon |
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[https://www.sciencedirect.com/science/article/pii/S0092867421000726 Massive expansion of human gut bacteriophage diversity] | [https://www.sciencedirect.com/science/article/pii/S0092867421000726 Massive expansion of human gut bacteriophage diversity] | ||
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|style="padding:.4em;"|21-24 | |style="padding:.4em;"|21-24 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|NY Kim |
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[https://science.sciencemag.org/content/366/6471/eaax9176 A metagenomic strategy for harnessing the chemical repertoire of the human microbiome] | [https://science.sciencemag.org/content/366/6471/eaax9176 A metagenomic strategy for harnessing the chemical repertoire of the human microbiome] | ||
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|style="padding:.4em;"|21-23 | |style="padding:.4em;"|21-23 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|IS Choi |
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[https://www.nature.com/articles/s41467-019-10927-1 Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences] | [https://www.nature.com/articles/s41467-019-10927-1 Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences] | ||
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|style="padding:.4em;"|21-22 | |style="padding:.4em;"|21-22 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|SA Kim |
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[https://www.nature.com/articles/s41564-018-0306-4 Gut microbiome structure and metabolic activity in inflammatory bowel disease] | [https://www.nature.com/articles/s41564-018-0306-4 Gut microbiome structure and metabolic activity in inflammatory bowel disease] | ||
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|style="padding:.4em;"|21-21 | |style="padding:.4em;"|21-21 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|HJ Kim |
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[https://www.nature.com/articles/s41591-020-01183-8 Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals] | [https://www.nature.com/articles/s41591-020-01183-8 Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals] | ||
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|style="padding:.4em;"|21-20 | |style="padding:.4em;"|21-20 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JY Ma |
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[https://www.nature.com/articles/s41467-020-18476-8 A predictive index for health status using species-level gut microbiome profiling] | [https://www.nature.com/articles/s41467-020-18476-8 A predictive index for health status using species-level gut microbiome profiling] | ||
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|style="padding:.4em;"|21-19 | |style="padding:.4em;"|21-19 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JH Cha |
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[https://www.nature.com/articles/s41586-019-1237-9 Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases] | [https://www.nature.com/articles/s41586-019-1237-9 Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases] | ||
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|style="padding:.4em;"|21-18 | |style="padding:.4em;"|21-18 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|SB Baek |
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[https://www.nature.com/articles/s41467-021-21475-y Gastrointestinal microbiota composition predicts peripheral inflammatory state during treatment of human tuberculosis] | [https://www.nature.com/articles/s41467-021-21475-y Gastrointestinal microbiota composition predicts peripheral inflammatory state during treatment of human tuberculosis] | ||
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− | |style="padding:.4em;"| | + | |style="padding:.4em;"|SR You |
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[https://www.sciencedirect.com/science/article/pii/S1931312820301694 Structure of the Mucosal and Stool Microbiome in Lynch Syndrome] | [https://www.sciencedirect.com/science/article/pii/S1931312820301694 Structure of the Mucosal and Stool Microbiome in Lynch Syndrome] | ||
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|style="padding:.4em;"|21-16 | |style="padding:.4em;"|21-16 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|HH Eom |
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[https://science.sciencemag.org/content/369/6506/936 Cross-reactivity between tumor MHC class 1-restricted antigens and an enterococcal bacteriophage] | [https://science.sciencemag.org/content/369/6506/936 Cross-reactivity between tumor MHC class 1-restricted antigens and an enterococcal bacteriophage] | ||
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|style="padding:.4em;"|21-15 | |style="padding:.4em;"|21-15 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JH Park |
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[https://www.nature.com/articles/s41564-020-00831-6 Bifidobacterium bifidum strains synergize with immune checkpoint inhibitors to reduce tumour burden in mice] | [https://www.nature.com/articles/s41564-020-00831-6 Bifidobacterium bifidum strains synergize with immune checkpoint inhibitors to reduce tumour burden in mice] | ||
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|style="padding:.4em;"|21-14 | |style="padding:.4em;"|21-14 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|MH Lee |
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[https://www.nature.com/articles/s41591-020-01223-3 The gut microbiome modulates the protective association between a Mediterranean diet and cardiometabolic disease risk] | [https://www.nature.com/articles/s41591-020-01223-3 The gut microbiome modulates the protective association between a Mediterranean diet and cardiometabolic disease risk] | ||
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− | |style="padding:.4em;"| | + | |style="padding:.4em;"|YY Jang |
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[https://www.nature.com/articles/s41467-019-14177-z Impact of commonly used drugs on the composition and metabolic function of the gut microbiota] | [https://www.nature.com/articles/s41467-019-14177-z Impact of commonly used drugs on the composition and metabolic function of the gut microbiota] | ||
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− | |style="padding:.4em;" rowspan= | + | |style="padding:.4em;" rowspan=1|2022/04/01 |
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|style="padding:.4em;"|21-12 | |style="padding:.4em;"|21-12 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|NY Kim |
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[https://www.sciencedirect.com/science/article/pii/S0092867420305638 Personalized Mapping of Drug Metabolism by the Human Gut Microbiome] | [https://www.sciencedirect.com/science/article/pii/S0092867420305638 Personalized Mapping of Drug Metabolism by the Human Gut Microbiome] | ||
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|style="padding:.4em;"|21-11 | |style="padding:.4em;"|21-11 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JM Lee |
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[https://www.cell.com/fulltext/S0092-8674(17)30107-1 Mining the Human Gut Microbiota for Immunomodulatory Organisms] | [https://www.cell.com/fulltext/S0092-8674(17)30107-1 Mining the Human Gut Microbiota for Immunomodulatory Organisms] | ||
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− | |style="padding:.4em;" rowspan= | + | |style="padding:.4em;" rowspan=1|2022/03/18 |
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|style="padding:.4em;"|21-10 | |style="padding:.4em;"|21-10 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JH Cha |
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[https://www.nature.com/articles/s41586-020-2095-1 Microbiome analyses of blood and tissues suggest cancer diagnostic approach] | [https://www.nature.com/articles/s41586-020-2095-1 Microbiome analyses of blood and tissues suggest cancer diagnostic approach] | ||
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|style="padding:.4em;"|21-9 | |style="padding:.4em;"|21-9 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JH Cha |
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[https://science.sciencemag.org/content/368/6494/973 The human tumor microbiome is composed of tumor type-specific intracellular bacteria] | [https://science.sciencemag.org/content/368/6494/973 The human tumor microbiome is composed of tumor type-specific intracellular bacteria] |
Revision as of 23:24, 10 March 2021
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 |