Difference between revisions of "Journal Club"
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[https://www.biorxiv.org/content/10.1101/2022.07.06.499075v1 Maast: genotyping thousands of microbial strains efficiently]  | [https://www.biorxiv.org/content/10.1101/2022.07.06.499075v1 Maast: genotyping thousands of microbial strains efficiently]  | ||
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[https://www.biorxiv.org/content/10.1101/2022.06.16.496510v2 MIDAS2: Metagenomic Intra-species Diversity Analysis System]  | [https://www.biorxiv.org/content/10.1101/2022.06.16.496510v2 MIDAS2: Metagenomic Intra-species Diversity Analysis System]  | ||
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[https://www.biorxiv.org/content/10.1101/2022.02.01.478746v2 Scalable microbial strain inference in metagenomic data using StrainFacts]  | [https://www.biorxiv.org/content/10.1101/2022.02.01.478746v2 Scalable microbial strain inference in metagenomic data using StrainFacts]  | ||
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[https://www.biorxiv.org/content/10.1101/2022.02.15.480535v1 StrainPanDA: linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data]  | [https://www.biorxiv.org/content/10.1101/2022.02.15.480535v1 StrainPanDA: linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data]  | ||
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[https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-022-01251-w Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation]  | [https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-022-01251-w Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation]  | ||
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[https://www.nature.com/articles/s41587-021-01102-3 Fast and accurate metagenotyping of the human gut microbiome with GT-Pro]  | [https://www.nature.com/articles/s41587-021-01102-3 Fast and accurate metagenotyping of the human gut microbiome with GT-Pro]  | ||
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[https://www.nature.com/articles/s41587-020-00797-0 inStrain profiles population microdiversity from metagenomic data and sensitively detects shared microbial strains]  | [https://www.nature.com/articles/s41587-020-00797-0 inStrain profiles population microdiversity from metagenomic data and sensitively detects shared microbial strains]  | ||
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[https://genome.cshlp.org/content/early/2021/07/22/gr.265058.120 Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment]  | [https://genome.cshlp.org/content/early/2021/07/22/gr.265058.120 Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment]  | ||
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[https://www.nature.com/articles/s41564-022-01121-z Identification of shared and disease-specific host gene–microbiome associations across human diseases using multi-omic integration]  | [https://www.nature.com/articles/s41564-022-01121-z Identification of shared and disease-specific host gene–microbiome associations across human diseases using multi-omic integration]  | ||
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[https://www.sciencedirect.com/science/article/pii/S193131282200049X Caudovirales bacteriophages are associated with improved executive function and memory in flies, mice, and humans]  | [https://www.sciencedirect.com/science/article/pii/S193131282200049X Caudovirales bacteriophages are associated with improved executive function and memory in flies, mice, and humans]  | ||
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[https://www.biorxiv.org/content/10.1101/2021.10.06.463341v2.full SynTracker: a synteny based tool for tracking microbial strains]  | [https://www.biorxiv.org/content/10.1101/2021.10.06.463341v2.full SynTracker: a synteny based tool for tracking microbial strains]  | ||
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[https://www.nature.com/articles/s41586-022-04648-7 Discovery of bioactive microbial gene products in inflammatory bowel disease]  | [https://www.nature.com/articles/s41586-022-04648-7 Discovery of bioactive microbial gene products in inflammatory bowel disease]  | ||
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[https://www.nature.com/articles/s41587-022-01226-0 Identification of antimicrobial peptides from the human gut microbiome using deep learning]  | [https://www.nature.com/articles/s41587-022-01226-0 Identification of antimicrobial peptides from the human gut microbiome using deep learning]  | ||
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[https://www.nature.com/articles/s43588-022-00247-8 Large-scale microbiome data integration enables robust biomarker identification]  | [https://www.nature.com/articles/s43588-022-00247-8 Large-scale microbiome data integration enables robust biomarker identification]  | ||
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[https://www.nature.com/articles/s41467-022-30512-3 Predicting cancer prognosis and drug response from the tumor microbiome]  | [https://www.nature.com/articles/s41467-022-30512-3 Predicting cancer prognosis and drug response from the tumor microbiome]  | ||
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[https://www.cell.com/cell-reports/pdf/S2211-1247(22)00770-7.pdf Thousands of small, novel genes predicted in global phage genomes]  | [https://www.cell.com/cell-reports/pdf/S2211-1247(22)00770-7.pdf Thousands of small, novel genes predicted in global phage genomes]  | ||
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[https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-022-01231-0 MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations]  | [https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-022-01231-0 MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations]  | ||
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Revision as of 14:56, 19 August 2022
| 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 |