Difference between revisions of "Journal Club"
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!scope="col" style="padding:.4em" | Presenter | !scope="col" style="padding:.4em" | Presenter | ||
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+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/10/02 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-51 | ||
+ | |style="padding:.4em;"|NY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41591-024-03067-7 Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/25 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-50 | ||
+ | |style="padding:.4em;"|JY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1186/s40168-024-01832-x Gut virome-wide association analysis identifes cross-population viral signatures for infammatory bowel disease] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/25 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-49 | ||
+ | |style="padding:.4em;"|YJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.cell.2024.03.034 Gut symbionts alleviate MASH through a secondary bile acid biosynthetic pathway] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/11 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-48-2 | ||
+ | |style="padding:.4em;"|JY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.48550/arXiv.1806.00064 Efficient Low-rank Multimodal Fusion with Modality-Specific Factors] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/11 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-48-1 | ||
+ | |style="padding:.4em;"|JY Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.48550/arXiv.1707.07250 Tensor Fusion Network for Multimodal Sentiment Analysis] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/11 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-47 | ||
+ | |style="padding:.4em;"|G Koh | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1186/s13059-024-03325-4 Gut microbiota DPP4-like enzymes are increased in type-2 diabetes and contribute to incretin inactivation] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/04 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-46 | ||
+ | |style="padding:.4em;"|SH Ahn | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [10.1093/bioinformatics/btz342 Deep learning with multimodal representation for pancancer prognosis prediction] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/04 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-45-2 | ||
+ | |style="padding:.4em;"|HJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [10.1109/TMI.2020.3021387 Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/09/04 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-45-1 | ||
+ | |style="padding:.4em;"|HJ Kim | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1016/j.ccell.2022.07.004 Pan-cancer integrative histology-genomic analysis via multimodal deep learning] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/28 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-44 | ||
+ | |style="padding:.4em;"|JY Ma | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.1038/s41592-022-01616-x BIONIC: biological network integration using convolutions] | ||
+ | |- | ||
+ | |style="padding:.4em;" rowspan=1|2024/08/28 | ||
+ | |style="padding:.4em;" rowspan=1|Microbiome | ||
+ | |style="padding:.4em;"|24-43 | ||
+ | |style="padding:.4em;"|JH Cha | ||
+ | |style="padding:.4em;text-align:left"| | ||
+ | [https://doi.org/10.48550/arXiv.2103.000205 Learning Transferable Visual Models From Natural Language Supervision] | ||
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Revision as of 16:08, 29 July 2024
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2024/10/02 | Microbiome | 24-51 | NY Kim | |
2024/09/25 | Microbiome | 24-50 | JY Kim | |
2024/09/25 | Microbiome | 24-49 | YJ Kim |
Gut symbionts alleviate MASH through a secondary bile acid biosynthetic pathway |
2024/09/11 | Microbiome | 24-48-2 | JY Kim |
Efficient Low-rank Multimodal Fusion with Modality-Specific Factors |
2024/09/11 | Microbiome | 24-48-1 | JY Kim | |
2024/09/11 | Microbiome | 24-47 | G Koh | |
2024/09/04 | Microbiome | 24-46 | SH Ahn |
[10.1093/bioinformatics/btz342 Deep learning with multimodal representation for pancancer prognosis prediction] |
2024/09/04 | Microbiome | 24-45-2 | HJ Kim |
[10.1109/TMI.2020.3021387 Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis] |
2024/09/04 | Microbiome | 24-45-1 | HJ Kim |
Pan-cancer integrative histology-genomic analysis via multimodal deep learning |
2024/08/28 | Microbiome | 24-44 | JY Ma | |
2024/08/28 | Microbiome | 24-43 | JH Cha |
Learning Transferable Visual Models From Natural Language Supervision |
2024/08/21 | Microbiome | 24-42 | NY Kim |
A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota |
2024/08/14 | Microbiome | 24-41 | YR Kim |
Accurate structure prediction of biomolecular interactions with AlphaFold 3 |
2024/08/14 | Microbiome | 24-40 | JY kim | |
2024/08/07 | Microbiome | 24-3ㅓ9 | WJ Kim |
Gut microbiome-metabolome interactions predict host condition |
2024/08/07 | Microbiome | 24-38 | G Koh |
Protein remote homology detection and structural alignment using deep learning |
2024/07/31 | Microbiome | 24-37 | SH Ahn |
A multi-kingdom collection of 33,804 reference genomes for the human vaginal microbiome |
2024/07/31 | Microbiome | 24-36 | HJ Kim | |
2024/07/24 | Microbiome | 24-35 | JY Ma | |
2024/07/24 | Microbiome | 24-34 | JH Cha |
Discovery of antimicrobial peptides in the global microbiome with machine learning |
2024/07/17 | Microbiome | 24-33 | NY Kim | |
2024/07/17 | Microbiome | 24-32 | YR Kim | |
2024/07/10 | Microbiome | 24-31 | JY Kim |
Interactions-based classification of a single microbial sample |
2024/07/10 | Microbiome | 24-30 | NY Kim | |
2024/07/03 | Microbiome | 24-29 | WJ Kim | |
2024/07/03 | Microbiome | 24-28 | G Koh | |
2024/06/26 | Microbiome | 24-27 | SH Ahn | |
2024/06/26 | Microbiome | 24-26 | HJ Kim | |
2024/06/19 | Microbiome | 24-25 | JY Ma |
Robustness of cancer microbiome signals over a broad range of methodological variation |
2024/06/19 | Microbiome | 24-24 | JY Cha |
A distinct Fusobacterium nucleatum clade dominates the colorectal cancer niche |
2024/06/05 | Microbiome | 24-22 | YR Kim |
A cryptic plasmid is among the most numerous genetic elements in the human gut |
2024/06/05 | Microbiome | 24-21 | JY Kim | |
2024/05/29 | Microbiome | 24-20 | WJ Kim | |
2024/05/29 | Microbiome | 24-19 | G Koh |
A host-microbiota interactome reveals extensive transkingdom connectivity |
2024/05/22 | Microbiome | 24-18 | SH Ahn | |
2024/05/22 | Microbiome | 24-17 | HJ Kim | |
2024/05/08 | Microbiome | 24-16 | JY Ma |
Large-scale computational analyses of gut microbial CAZyme repertoires enabled by Cayman |
2024/05/08 | Microbiome | 24-15 | JH Cha | |
2024/05/01 | Microbiome | 24-14 | NY Kim |
Gut microbial structural variation associates with immune checkpoint inhibitor response |
2024/05/01 | Microbiome | 24-13 | YR Kim | |
2024/04/24 | Microbiome | 24-12 | JY Kim | |
2024/04/24 | Microbiome | 24-11 | WJ Kim |
Disease-specific loss of microbial cross feeding interactions in the human gut |
2024/04/03 | Microbiome | 24-7 | JY Ma |
Multigroup analysis of compositions of microbiomes with covariate adjustments and repeated measures |
2024/04/03 | Microbiome | 24-9 | SH Ahn |
Microdiversity of the vaginal microbiome is associated with preterm birth |
2024/03/27 | Microbiome | 24-8 | HJ Kim |
Large language models improve annotation of prokaryotic viral proteins |
2024/03/27 | Microbiome | 24-10 | G Koh | |
2024/03/20 | Microbiome | 24-6-2 | JH Cha |
Visualizing ’omic feature rankings and log-ratios using Qurro |
2024/03/20 | Microbiome | 24-6-1 | JH Cha |
Establishing microbial composition measurement standards with reference frames |
2024/03/20 | Microbiome | 24-5 | NY Kim | |
2024/03/13 | Microbiome | 24-4 | YR Kim | |
2024/03/13 | Microbiome | 24-3 | JY Kim |
Effective binning of metagenomic contigs using contrastive multi-view representation learning |
2024/03/06 | Microbiome | 24-2 | WJ Kim |
Polarization of microbial communities between competitive and cooperative metabolism |
2024/03/06 | Microbiome | 24-1-2 | G Koh |
Metagenomic Insight into The Global Dissemination of The Antibiotic Resistome |
2024/03/06 | Microbiome | 24-1-1 | G Koh |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2024/06/18 | Single-cell | 24-32 | EB Hong |
Spatial transcriptomics reveal neuron–astrocyte synergy in long-term memory |
2024/06/18 | Single-cell | 24-31 | JJ Heo |
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses |
2024/06/18 | Single-cell | 24-30 | SM Han |
Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution |
2024/06/18 | Single-cell | 24-29 | HJ Choi | |
2024/06/11 | Single-cell | 24-28 | SA Choi | |
2024/06/11 | Single-cell | 24-27 | HJ Cha |
Cell-type-specific responses to fungal infection in plants revealed by single-cell transcriptomics |
2024/06/11 | Single-cell | 24-26 | YK Jung | |
2024/06/11 | Single-cell | 24-25 | HJ Lee | |
2024/06/04 | Single-cell | 24-24 | HK Lee |
Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas |
2024/06/04 | Single-cell | 24-23 | JI Lee |
Multimodal spatiotemporal phenotyping of human retinal organoid development |
2024/06/04 | Single-cell | 24-22 | JH Lee | |
2024/06/04 | Single-cell | 24-21 | JH Lee |
A single-cell analysis of the Arabidopsis vegetative shoot apex |
2024/05/28 | Single-cell | 24-20 | JH Lee |
Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq |
2024/05/28 | Single-cell | 24-19 | YH Lee | |
2024/05/28 | Single-cell | 24-18 | EB Yu | |
2024/05/28 | Single-cell | 24-17 | DY Won |
Spatial metatranscriptomics resolves host–bacteria–fungi interactomes |
2024/05/21 | Single-cell | 24-16 | SG Oh | |
2024/05/21 | Single-cell | 24-15 | SY Park | |
2024/05/21 | Single-cell | 24-14 | HS Moon | |
2024/05/21 | Single-cell | 24-13 | JH Nam |
Spatial cellular architecture predicts prognosis in glioblastoma |
2024/05/14 | Single-cell | 24-12 | HS Na | |
2024/05/14 | Single-cell | 24-11 | PK Kim |
Transcriptional adaptation of olfactory sensory neurons to GPCR identity and activity |
2024/05/14 | Single-cell | 24-10 | SH Kwon | |
2024/05/14 | Single-cell | 24-9 | Q Zhen | |
2024/05/07 | Single-cell | 24-8 | CR Leenaars | |
2024/05/07 | Single-cell | 24-7 | YR Kim | |
2024/05/07 | Single-cell | 24-6 | JY Kim |
Spatial transcriptomics landscape of lesions from non-communicable inflammatory skin diseases |
2024/05/07 | Single-cell | 24-5 | WJ Kim |
Neuregulin 4 suppresses NASH-HCC development by restraining tumor-prone liver microenvironment |
2024/04/23 | Single-cell | 24-4 | G Koh |
Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer’s disease |
2024/04/23 | Single-cell | 24-3 | SH Ahn | |
2024/04/23 | Single-cell | 24-2 | EJ Sung | |
2024/04/23 | Single-cell | 24-1 | HJ Kim |
Date | Team | Paper index |
Presenter | Paper title |
---|---|---|---|---|
2023/08/30 | Single-cell | 23-24 | JW Yu | |
2023/08/09 | Single-cell | 23-23 | IS Choi |
Major data analysis errors invalidate cancer microbiome findings |
2023/08/02 | Single-cell | 23-22 | EJ Sung | |
2023/07/26 | Single-cell | 23-21 | G Koh | |
2023/07/19 | Single-cell | 23-20 | JW Yu |
Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression |
2023/07/12 | Single-cell | 23-19 | JH Cha |
DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data |
2023/07/05 | Single-cell | 23-18 | SB Baek |
Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance |
2023/06/28 | Single-cell | 23-17 | EJ Sung | |
2023/06/21 | Single-cell | 23-16 | IS Choi | |
2023/06/14 | Single-cell | 23-15 | G Koh | |
2023/05/31 | Single-cell | 23-14 | JW Yu |
Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma |
2023/05/24 | Single-cell | 23-13 | JH Cha | |
2023/05/17 | Single-cell | 23-12 | SB Baek | |
2023/05/10 | Single-cell | 23-11 | EJ Sung |
Supervised discovery of interpretable gene programs from single-cell data |
2023/05/03 | Single-cell | 23-10 | IS Choi |
Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer |
2023/04/26 | Single-cell | 23-9 | G Koh | |
2023/03/22 | Single-cell | 23-8 | JW Yu |
MetaTiME: Meta-components of the Tumor Immune Microenvironment |
2023/03/08 | Single-cell | 23-7 | JH Cha | |
2023/02/21 | Single-cell | 23-6 | SB Baek | |
2023/02/14 | Single-cell | 23-5 | EJ Sung |
A T cell resilience model associated with response to immunotherapy in multiple tumor types |
2022/01/31 | Single-cell | 23-4 | IS Choi | |
2023/01/25 | Single-cell | 23-3 | G Koh | |
2023/01/17 | Single-cell | 23-2 | JW Yu |
Pan-cancer integrative histology-genomic analysis via multimodal deep learning |
2023/01/11 | Single-cell | 23-1 | JH Cha |
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 |