Difference between revisions of "Journal Club"
From Bioinformatics Lab
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− | |style="padding:.4em;" rowspan=2|2017/06/ | + | |style="padding:.4em;" rowspan=2|2017/06/14 |
− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-38 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|HJ Han |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1126%2Fscience.aaf8399 Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1126%2Fscience.aaf8399 Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy.] | ||
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− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-37 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JW Cho |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fng.3581 Landscape of tumor-infiltrating T cell repertoire of human cancers.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fng.3581 Landscape of tumor-infiltrating T cell repertoire of human cancers.] | ||
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− | |style="padding:.4em;" rowspan=2|2017/ | + | |style="padding:.4em;" rowspan=2|2017/06/07 |
− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-36 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|JW Cho |
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[http://biorxiv.org/content/early/2015/09/01/025908 The landscape of T cell infiltration in human cancer and its association with antigen presenting gene expression.] | [http://biorxiv.org/content/early/2015/09/01/025908 The landscape of T cell infiltration in human cancer and its association with antigen presenting gene expression.] | ||
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− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-35 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|KS Kim |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.08.052 A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.08.052 A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells.] | ||
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− | |style="padding:.4em;" rowspan=2|2017/05/ | + | |style="padding:.4em;" rowspan=2|2017/05/31 |
− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-34 |
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[http://www.tandfonline.com/doi/full/10.1080/2162402X.2016.1253654 Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis.] | [http://www.tandfonline.com/doi/full/10.1080/2162402X.2016.1253654 Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis.] | ||
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− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-33 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|MY Lee |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.celrep.2016.03.075 Genomic Correlates of Immune-Cell Infiltrates in Colorectal Carcinoma.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.celrep.2016.03.075 Genomic Correlates of Immune-Cell Infiltrates in Colorectal Carcinoma.] | ||
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− | |style="padding:.4em;" rowspan=2|2017/05/ | + | |style="padding:.4em;" rowspan=2|2017/05/24 |
− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-32 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|DS Bae |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.02.065 Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.02.065 Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma.] | ||
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− | |style="padding:.4em;"|17- | + | |style="padding:.4em;"|17-31 |
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|MY Lee |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.celrep.2016.12.019 Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.celrep.2016.12.019 Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade.] | ||
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− | |style="padding:.4em;" rowspan= | + | |style="padding:.4em;" rowspan=2|2017/05/17 |
+ | |style="padding:.4em;"|17-30 | ||
+ | |style="padding:.4em;"|EB Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.12.022 Systemic Immunity Is Required for Effective Cencer Immunotherapy.] | ||
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|style="padding:.4em;"|17-29 | |style="padding:.4em;"|17-29 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|CY Kim |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.10.020 Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.10.020 Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity.] | ||
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+ | |style="padding:.4em;" rowspan=3|2017/05/10 | ||
|style="padding:.4em;"|17-28 | |style="padding:.4em;"|17-28 | ||
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− | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10. | + | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2FNMETH.4177 Pooled CRISPR screening with single-cell transcriptome readout.] |
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− | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.11. | + | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.11.039 Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq.] |
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|style="padding:.4em;" rowspan=2|2017/04/12 | |style="padding:.4em;" rowspan=2|2017/04/12 | ||
|style="padding:.4em;"|17-22 | |style="padding:.4em;"|17-22 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|SH Lee |
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− | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10. | + | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016%2Fj.cell.2016.11.038 Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens.] |
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|style="padding:.4em;"|17-21 | |style="padding:.4em;"|17-21 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|CY Kim |
|style="padding:.4em;text-align:left"| | |style="padding:.4em;text-align:left"| | ||
− | [https://www.ncbi.nlm.nih.gov/pubmed/ | + | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fnbt.3569 Wishbone identifies bifurcating developmental trajectories from single-cell data.] |
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|style="padding:.4em;" rowspan=2|2017/04/05 | |style="padding:.4em;" rowspan=2|2017/04/05 | ||
|style="padding:.4em;"|17-20 | |style="padding:.4em;"|17-20 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|KS Kim |
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[http://biorxiv.org/content/early/2017/02/21/110668 Reversed graph embedding resolves complex single-cell developmental trajectories.] | [http://biorxiv.org/content/early/2017/02/21/110668 Reversed graph embedding resolves complex single-cell developmental trajectories.] | ||
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|style="padding:.4em;"|17-19 | |style="padding:.4em;"|17-19 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|SH Lee |
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[https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fnmeth.4150 Single-cell mRNA quantification and differential analysis with Census.] | [https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fnmeth.4150 Single-cell mRNA quantification and differential analysis with Census.] | ||
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|style="padding:.4em;"|17-17 | |style="padding:.4em;"|17-17 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|DS Bae |
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[https://www.ncbi.nlm.nih.gov/pubmed/26051941 Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis.] | [https://www.ncbi.nlm.nih.gov/pubmed/26051941 Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis.] | ||
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|style="padding:.4em;"|17-15 | |style="padding:.4em;"|17-15 | ||
− | |style="padding:.4em;"| | + | |style="padding:.4em;"|EB Kim |
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[https://www.ncbi.nlm.nih.gov/pubmed/27281220 Dissecting direct reprogramming from fibroblast to neuron using single-cell RNA-seq.] | [https://www.ncbi.nlm.nih.gov/pubmed/27281220 Dissecting direct reprogramming from fibroblast to neuron using single-cell RNA-seq.] |
Revision as of 17:46, 9 March 2017
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