Difference between revisions of "Journal Club"
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[https://pubmed.ncbi.nlm.nih.gov/34852236/ Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses] | [https://pubmed.ncbi.nlm.nih.gov/34852236/ Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses] | ||
|} | |} | ||
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+ | {|class=wikitable style="text-align:center;" | ||
+ | |+style="text-align:left;font-size:12pt" | 2022-1st semester scOmics | ||
+ | |- | ||
+ | !scope="col" style="padding:.4em" | Date | ||
+ | !scope="col" style="padding:.4em" | Team | ||
+ | !scope="col" style="padding:.4em" | Paper<br/>index | ||
+ | !scope="col" style="padding:.4em" | Presenter | ||
+ | !scope="col" style="padding:.4em" | Paper title | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/06/17 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-36 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2022.02.05.479217 Biologically informed deep learning to infer gene program activity in single cells] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/06/10 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-35 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2021.10.17.464750 SIMBA: SIngle-cell eMBedding Along with features] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/06/03 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-34 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34462589/ Mapping single-cell data to reference atlases by transfer learning] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/05/27 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-33 | ||
+ | |style="padding:.4em;"|JW Yu | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1101/2021.10.31.466532 Pan-cancer mapping of single T cell profiles reveals a TCF1:CXCR6-CXCL16 regulatory axis essential for effective anti-tumor immunity] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/05/20 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-32 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.patter.2022.100443 EMBEDR: Distinguishing signal from noise in single-cell omics data] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/05/13 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-31 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34845454/ Identifying disease-critical cell types and cellular processes across the human body by integration of single-cell profiles and human genetics] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/05/06 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-30 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34675423/ Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/04/29 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-29 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34426704/ Integrating T cell receptor sequences and transcriptional profiles by clonotype neighbor graph analysis (CoNGA)] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/04/22 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-28 | ||
+ | |style="padding:.4em;"|JW Yu | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34986867/ Hepatocellular carcinoma patients with high circulating cytotoxic T cells and intra-tumoral immune signature benefit from pembrolizumab: results from a single-arm phase 2 trial] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/04/15 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-27 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/35199064/ Effect of imputation on gene network reconstruction from single-cell RNA-seq data] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/04/08 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-26 | ||
+ | |style="padding:.4em;"|IS Choi | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/35105355/ Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/04/01 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-25 | ||
+ | |style="padding:.4em;"|SB Baek | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/35172892/ Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/03/25 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-24 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34663807/ Single cell T cell landscape and T cell receptor repertoire profiling of AML in context of PD-1 blockade therapy] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/03/18 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-23 | ||
+ | |style="padding:.4em;"|JW Yu | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34594031/ Systematic investigation of cytokine signaling activity at the tissue and single-cell levels] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2022/03/04 | ||
+ | |style="padding:.4em;" rowspan=1|Single-cell | ||
+ | |style="padding:.4em;"|22-22 | ||
+ | |style="padding:.4em;"|EJ Sung | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://pubmed.ncbi.nlm.nih.gov/34852236/ Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses] | ||
+ | |} | ||
+ | |||
+ | --------- | ||
{|class=wikitable style="text-align:center;" | {|class=wikitable style="text-align:center;" |
Revision as of 11:14, 28 March 2022
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2022/06/17 | Single-cell | 22-36 | IS Choi |
Biologically informed deep learning to infer gene program activity in single cells |
2022/06/10 | Single-cell | 22-35 | SB Baek | |
2022/06/03 | Single-cell | 22-34 | JH Cha |
Mapping single-cell data to reference atlases by transfer learning |
2022/05/27 | Single-cell | 22-33 | JW Yu | |
2022/05/20 | Single-cell | 22-32 | EJ Sung |
EMBEDR: Distinguishing signal from noise in single-cell omics data |
2022/05/13 | Single-cell | 22-31 | IS Choi | |
2022/05/06 | Single-cell | 22-30 | SB Baek | |
2022/04/29 | Single-cell | 22-29 | JH Cha | |
2022/04/22 | Single-cell | 22-28 | JW Yu | |
2022/04/15 | Single-cell | 22-27 | EJ Sung |
Effect of imputation on gene network reconstruction from single-cell RNA-seq data |
2022/04/08 | Single-cell | 22-26 | IS Choi | |
2022/04/01 | Single-cell | 22-25 | SB Baek | |
2022/03/25 | Single-cell | 22-24 | JH Cha | |
2022/03/18 | Single-cell | 22-23 | JW Yu |
Systematic investigation of cytokine signaling activity at the tissue and single-cell levels |
2022/03/04 | Single-cell | 22-22 | EJ Sung |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2022/06/17 | Single-cell | 22-36 | IS Choi |
Biologically informed deep learning to infer gene program activity in single cells |
2022/06/10 | Single-cell | 22-35 | SB Baek | |
2022/06/03 | Single-cell | 22-34 | JH Cha |
Mapping single-cell data to reference atlases by transfer learning |
2022/05/27 | Single-cell | 22-33 | JW Yu | |
2022/05/20 | Single-cell | 22-32 | EJ Sung |
EMBEDR: Distinguishing signal from noise in single-cell omics data |
2022/05/13 | Single-cell | 22-31 | IS Choi | |
2022/05/06 | Single-cell | 22-30 | SB Baek | |
2022/04/29 | Single-cell | 22-29 | JH Cha | |
2022/04/22 | Single-cell | 22-28 | JW Yu | |
2022/04/15 | Single-cell | 22-27 | EJ Sung |
Effect of imputation on gene network reconstruction from single-cell RNA-seq data |
2022/04/08 | Single-cell | 22-26 | IS Choi | |
2022/04/01 | Single-cell | 22-25 | SB Baek | |
2022/03/25 | Single-cell | 22-24 | JH Cha | |
2022/03/18 | Single-cell | 22-23 | JW Yu |
Systematic investigation of cytokine signaling activity at the tissue and single-cell levels |
2022/03/04 | Single-cell | 22-22 | EJ Sung |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2022/02/25 | Single-cell | 22-21 | SB Baek |
MultiMAP: dimensionality reduction and integration of multimodal data |
2022/02/18 | Single-cell | 22-20 | IS Choi | |
2022/02/11 | Single-cell | 22-19 | JH Cha | |
2022/02/04 | Single-cell | 22-18 | IS Choi | |
2022/01/28 | Single-cell | 22-17 | EJ Sung | |
2022/01/28 | Single-cell | 22-16 | JH Cha |
Pan-cancer single-cell landscape of tumor-infiltrating T cells |
2022/01/14 | Single-cell | 22-15 | JW Yu |
Atlas of clinically distinct cell states and ecosystems across human solid tumors |
2022/01/07 | Single-cell | 22-14 | SB Baek |
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 |