Difference between revisions of "Journal Club"
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|style="padding:.4em;"|G Koh | |style="padding:.4em;"|G Koh | ||
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[https://www.nature.com/articles/s41588-022-01141-9 Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment] | [https://www.nature.com/articles/s41588-022-01141-9 Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment] | ||
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|style="padding:.4em;"|JW Yu | |style="padding:.4em;"|JW Yu | ||
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[https://www.biorxiv.org/content/10.1101/2022.08.05.502989v1 MetaTiME: Meta-components of the Tumor Immune Microenvironment] | [https://www.biorxiv.org/content/10.1101/2022.08.05.502989v1 MetaTiME: Meta-components of the Tumor Immune Microenvironment] | ||
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|style="padding:.4em;"|JH Cha | |style="padding:.4em;"|JH Cha | ||
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[https://www.nature.com/articles/s41590-022-01262-7 Pre-encoded responsiveness to type I interferon in the peripheral immune system defines outcome of PD1 blockade therapy] | [https://www.nature.com/articles/s41590-022-01262-7 Pre-encoded responsiveness to type I interferon in the peripheral immune system defines outcome of PD1 blockade therapy] | ||
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|style="padding:.4em;"|SB Baek | |style="padding:.4em;"|SB Baek | ||
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[https://www.biorxiv.org/content/10.1101/2022.03.16.484513v1 Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating T cells] | [https://www.biorxiv.org/content/10.1101/2022.03.16.484513v1 Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating T cells] | ||
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|style="padding:.4em;"|EJ Sung | |style="padding:.4em;"|EJ Sung | ||
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[https://www.nature.com/articles/s41591-022-01799-y A T cell resilience model associated with response to immunotherapy in multiple tumor types] | [https://www.nature.com/articles/s41591-022-01799-y A T cell resilience model associated with response to immunotherapy in multiple tumor types] | ||
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|style="padding:.4em;"|IS Choi | |style="padding:.4em;"|IS Choi | ||
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[https://www.nature.com/articles/s41588-022-01134-8 Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment] | [https://www.nature.com/articles/s41588-022-01134-8 Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment] | ||
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|style="padding:.4em;"|G Koh | |style="padding:.4em;"|G Koh | ||
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[https://pubmed.ncbi.nlm.nih.gov/35649411/ Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases] | [https://pubmed.ncbi.nlm.nih.gov/35649411/ Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases] | ||
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|style="padding:.4em;"|JW Yu | |style="padding:.4em;"|JW Yu | ||
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[https://www.sciencedirect.com/science/article/pii/S1535610822003178 Pan-cancer integrative histology-genomic analysis via multimodal deep learning] | [https://www.sciencedirect.com/science/article/pii/S1535610822003178 Pan-cancer integrative histology-genomic analysis via multimodal deep learning] | ||
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|style="padding:.4em;"|JH Cha | |style="padding:.4em;"|JH Cha | ||
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[https://pubmed.ncbi.nlm.nih.gov/35803260/ Tissue-resident memory and circulating T cells are early responders to pre-surgical cancer immunotherapy] | [https://pubmed.ncbi.nlm.nih.gov/35803260/ Tissue-resident memory and circulating T cells are early responders to pre-surgical cancer immunotherapy] | ||
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|+style="text-align:left;font-size:12pt" | 2023 Microbiome | |||
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|style="padding:.4em;" rowspan=1|Microbiome | |||
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|style="padding:.4em;"|NY Kim | |||
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[https://www.nature.com/articles/s41564-022-01157-1 Phage–host coevolution in natural populations] | |||
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|style="padding:.4em;" rowspan=1|Microbiome | |||
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|style="padding:.4em;"|SH Lee | |||
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[https://www.nature.com/articles/s41467-022-29968-0 A randomized controlled trial for response of microbiome network to exercise and diet intervention in patients with nonalcoholic fatty liver disease] | |||
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|style="padding:.4em;" rowspan=1|Microbiome | |||
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|style="padding:.4em;"|SH Ahn | |||
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[https://www.biorxiv.org/content/10.1101/2022.05.19.492684v1 Scalable power analysis and effect size exploration of microbiome community differences with Evident] | |||
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|style="padding:.4em;"|HJ Kim | |||
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[https://www.biorxiv.org/content/10.1101/2022.08.05.502982v1 Phanta: Phage-inclusive profiling of human gut metagenomes] | |||
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|style="padding:.4em;" rowspan=1|Microbiome | |||
|style="padding:.4em;"|23-1 | |||
|style="padding:.4em;"|JH Cha | |||
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[https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010373 Computational approach to modeling microbiome landscapes associated with chronic human disease progression] | |||
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[https://www.nature.com/articles/nmeth.3802 Strain-level microbial epidemiology and population genomics from shotgun metagenomics] | [https://www.nature.com/articles/nmeth.3802 Strain-level microbial epidemiology and population genomics from shotgun metagenomics] | ||
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