Difference between revisions of "Journal Club"
Line 123: | Line 123: | ||
!scope="col" style="padding:.4em" | Paper title | !scope="col" style="padding:.4em" | Paper title | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/09/ | + | |style="padding:.4em;" rowspan=1|2022/09/22 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-28 | |style="padding:.4em;"|22-28 | ||
Line 130: | Line 130: | ||
[https://www.nature.com/articles/s41586-022-04718-w Extricating human tumour immune alterations from tissue inflammation] | [https://www.nature.com/articles/s41586-022-04718-w Extricating human tumour immune alterations from tissue inflammation] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/09/ | + | |style="padding:.4em;" rowspan=1|2022/09/15 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-27 | |style="padding:.4em;"|22-27 | ||
Line 137: | Line 137: | ||
[https://www.biorxiv.org/content/10.1101/2021.12.06.471401v1 MIRA: Joint regulatory modeling of multimodal expression and chromatin accessibility in single cells] | [https://www.biorxiv.org/content/10.1101/2021.12.06.471401v1 MIRA: Joint regulatory modeling of multimodal expression and chromatin accessibility in single cells] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/09/ | + | |style="padding:.4em;" rowspan=1|2022/09/08 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-26 | |style="padding:.4em;"|22-26 | ||
Line 144: | Line 144: | ||
[https://www.nature.com/articles/s41587-021-01091-3 Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data] | [https://www.nature.com/articles/s41587-021-01091-3 Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/ | + | |style="padding:.4em;" rowspan=1|2022/09/01 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-25 | |style="padding:.4em;"|22-25 | ||
Line 151: | Line 151: | ||
[https://www.biorxiv.org/content/10.1101/2022.06.15.495325v1 T cell receptor convergence is an indicator of antigen-specific T cell response in cancer immunotherapies] | [https://www.biorxiv.org/content/10.1101/2022.06.15.495325v1 T cell receptor convergence is an indicator of antigen-specific T cell response in cancer immunotherapies] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/08/ | + | |style="padding:.4em;" rowspan=1|2022/08/25 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-24 | |style="padding:.4em;"|22-24 | ||
Line 158: | Line 158: | ||
[https://www.sciencedirect.com/science/article/pii/S1535610822000654 Immune phenotypic linkage between colorectal cancer and liver metastasis] | [https://www.sciencedirect.com/science/article/pii/S1535610822000654 Immune phenotypic linkage between colorectal cancer and liver metastasis] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/08/ | + | |style="padding:.4em;" rowspan=1|2022/08/18 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-22 | |style="padding:.4em;"|22-22 | ||
Line 165: | Line 165: | ||
[https://www.nature.com/articles/s43018-022-00356-3 Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology] | [https://www.nature.com/articles/s43018-022-00356-3 Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology] | ||
|- | |- | ||
− | |style="padding:.4em;" rowspan=1|2022/08/ | + | |style="padding:.4em;" rowspan=1|2022/08/11 |
|style="padding:.4em;" rowspan=1|Single-cell | |style="padding:.4em;" rowspan=1|Single-cell | ||
|style="padding:.4em;"|22-23 | |style="padding:.4em;"|22-23 |
Revision as of 09:27, 16 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 |