Bioinformatics

[2024.01.12] Jaemin Jeon (presentation link) Keyword: TCR, 3D structure
•DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis. Science Advances, 9 (32)  (2023) (link)

[2024.01.19] Ari Hong(presentation link) Keyword:  RNA velocity
• A relay velocity model infers cell-dependent RNA velocity, Nature Biotechnology  42 (2023) (link)

[2024.01.19] Yooeun Kim (presentation link) Keyword: Perturb-seq, GNN
• Predicting transcriptional outcomes of novel multigene perturbations with GEARS. Nature Biotechnology   (2023) (link)

[2024.01.26] Hongseok Ha(presentation link) Keyword: genetic priority score (GPS0)
•Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications, Nature Genetics 55 (51-59) (2024) (link)

[2024.1.26] SeungHo Han(presentation link) Keyword: WGS, Clinical data integration
•Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme, Nature Medicine 30, 279-280 (2024) (link)

[2024.02.02] Hoeyoung Kim (presentation link) Keyword: Multimodal, Data fusion, Survival analysis
• Multimodal deep learning to predict prognosis in adult and pediatric brain tumors, Communications Medicine,  3 (44) (2023) (link)

[2024.02.16] Kyeonghun Jeong (presentation link) Keyword: single cell transcriptomics
•Population-level integration of single-cell datasets enables multi-scale analysis across sample Nature Methods (2023) (link)
[2024.02.16] Donghee Kim (presentation link) Keyword: neural ODE
•Neural Ordinary Differneital Equeations arxiv (2019) (link)

[2024.2.23] Jaemin Jeon (presentation link) Keyword: BERT, TCR, MHC
•Accurate TCR-pMHC interaction prediction using a BERT-based transfer learning method  Breifings Bioinformatics, 25(1) (2024) (link)

[2024.02.23] Ari Hong(presentation link) Keyword:  RNA velocity
•Multi-omic single-cell velocity models epigenome–transcriptome interactions and improves cell fate prediction,  Nature Biotechnology  42 (2022) (link)

[2024.03.06] Yooeun Kim (presentation link) Keyword: Perturbation prediction, Autoencoder
• Predicting cellular responses to complex perturbations in high‐throughput screens. Molecular Systems Biology   (2023) (link)

[2024.03.20] Hongseok Ha(presentation link) Keyword: single-cell omics
•Advances in single-cell omics and multiomics for high-resolution molecular profiling, Experimental & Molecular Medicine (2024) (link)

[2024.03.27] SeungHo Han(presentation link) Keyword: GSEA, DGSEA
•Differential Gene Set Enrichment Analysis: a statistical approach to quantify the relative enrichment of two gene sets, Oxford Bioinformatics  36 (21) (2020) (link)

[2024.04.03] Hoeyoung Kim (presentation link) Keyword: Metatranscriptomics, Host-pathogen interaction
• Spatial metatranscriptomics resolves host–bacteria–fungi interactomes, Nature Biotechnology,  43 (2023) (link)

[2024.04.17] Suwan Yu (presentation link) Keyword: Survival Prediction, Multi-modal, Histology Image
•Pan-cancer integrative histology-genomic analysis via multimodal deep learning, Cancer Cell,  40(8) (2022) (link)

[2024.04.24] Kyeonghun Jeong (presentation link) Keyword: drug response, transfer learning, single-cell omics
•Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data Nature Communications (2022) (link)

[2023.01.09] Kyeonghun Jeong (presentation link) Keyword: Pathway score, Gene set analysis
• GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics 14, 7 (2013) (link)

[2023.01.16] Yooeun Kim (presentation link) Keyword: Mutational signature, Methodology
• Deciphering signatures of mutational processes operative in human cancer. Cell Reports 3, 1 (2013) (link)

[2023.02.17] Kyeonghun Jeong (presentation link) Keyword: Pathway score, scATAC-seq, scRNA-seq
• UniPath: a uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles. Nucleic Acids Research 49, 3 (2021) (link)

[2023.02.24] Sunah Yang (presentation link) Keyword: : Multimodal, Deep learning, Histology, Genomic data
• Pan-cancer integrative histology-genomic analysis via multimodal deep learning. Cancer Cell 40, 8 (2022) (link)

[2023.02.24] Suwan Yu (presentation link) Keyword: scRNAseq, Machine Learning, Tumor annotation
• Identifying tumor cells at the single-cell level using machine learning. Genome Biology 23, 123 (2022) (link)

[2023. 02. 27] Ari Hong (presentation link) Keyword: Image Mass Cytometry (IMC), Single-cell, Spatial data
• histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nature Methods 14 (2017) (link)
• Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy. Science Immunology 7, 70 (2022) (link)

[2023.03.08] Yooeun Kim (presentation link) Keyword: Multiomics, Longitudinal
• Interpretation of network-based integration from multi-omics longitudinal data, Nucleic Acids Research 50, 5 (2022) (link)

[2023.03.08] Seulbi Lee (presentation link) Keyword: scRNA-seq, trajectory
• Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression Nature communications 12 (2021) (link)

[2023.03.15] Jaemin Jeon (presentation link) Keyword: TCRseq
• De novo prediction of cancer-associated T cell receptors for noninvasive cancer detection, Science translation 12 (2021) (link)
• Use of machine learning to identify a T cell response to SARS-CoV-2,  Cell reports medicine 2, 2 (2021) (link)
• TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-xbinding analyses, preprint  (2021) (link)

[2023.03.15] Suwan Yu (presentation link) Keyword: TCRseq, CNN, VAE
• DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires, Nature Communications 12, 1(2021) (link)

[2023.03.22] Hongseok Ha(presentation link) Keyword: CITE-seq
• High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq, Nature Biotechnology 12, 1(2023) (link)

[2023.03.22] SoYon Park (presentation link) Keyword: scRNAseq, GNN
• scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses Nature Communications 12, 1(2021) (link)

[2023.03.29] Kyeonghun Jeong (presentation link) Keyword: Multimodal
• Spatial epigenome–transcriptome co-profiling of mammalian tissues. Nature (2023) (link)

[2023.03.29] SoYon Park (presentation link) Keyword: singlecell, multiomics, GNN
• Single-cell biological network inference using a heterogeneous graph transformer, Nature Communications 14 (2023) (link)

[2023.04.05] Ari Hong(presentation link) Keyword: spatial omics, CVAE, GNN
• Modeling intercellular communication in tissues using spatial graphs of cells, Nature Biotechnology  41 (2022) (link)

[2023.04.05] Yooeun Kim(presentation link) Keyword: singlecell, multiomics, GNN
• Single-cell biological network inference using a heterogeneous graph transformer, Nature Communications 14 (2023) (link)

[2023.04.05] Hoeyoung Kim (presentation link) Keyword: Genome assembly, Repeat graph
• Assembly of long, error-prone reads using repeat graphs, Nature Biotechnology  37(5) (2019) (link)

[2023.04.12] Jaemin Jeon (presentation link) Keyword: TCRseq
• TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs, Bioinformatics 39 (2023) (link)

[2023.04.12] SoYon Park (presentation link) Keyword: singlecell, multiomics, GNN
• Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images, Nucleic Acid Reports 49 (2021) (link)
• CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data, Nucleic Acid Reports 50 (2021) (link)
• GeneDART: Extending gene coverage in image-based spatial transcriptomics by deep learning-based domain adaptation with barcode-based RNA-sequencing data, preprint (link)
• Mapping cell types in the tumor microenvironment from tissue images via deep learning trained by spatial transcriptomics of lung adenocarcinoma, preprint (link)
• spSeudoMap: cell type mapping of spatial transcriptomics using unmatched single-cell RNA-seq data, Genome Medicine 15 2023 (link)

[2023.05.10] Kyeonghun Jeong (presentation link) Keyword: Spatial transcriptomics, single cell transcriptomics, VAE, multiomics
• The covariance environment defines cellular niches for spatial inference. preprint  (2023) (link)

[2023.05.17] Hongseok Ha(presentation link) Keyword: somatic mutation, L1 retrotransposition
•Widespread somatic L1 retrotransposition in normal colorectal epithelium , Nature  617(2023) (link)

[2023.05.17] Sunah Yang (presentation link) Keyword: Spatial transcriptomics, Cell deconvolution
•Cell2location maps fine-grained cell types in spatial transcriptomics. Nature Biotechnology 40 (2022) (link)

[2023.05.24] SeoYoon Park (presentation link) Keyword: alternative splicing, alternative polyadenylation
•Alternative splicing and alternative polyadenylation define tumor immune microenvironment and pharmacogenomic landscape in clear cell renal carcinoma, Molecular Therapy Nucleic Acids 27 (2022) (link)

[2023.05.24] Suwan Yu (presentation link) Keyword: TCRseq, single cell
• Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics, Nature Methods 18 (2021) (link)

[2023.05.31] Jaemin Jeon (presentation link) Keyword: Open set recognition
• Learning Placeholders for Open-Set Recognition, Computer Vision Pattern Recognition  (2021) (link)

[2023. 06.21] Ari Hong (presentation link) Keyword: isoform, TSS, APA, long read sequencing
• Sites of transcription initiation drive mRNA isoform selection(2023) (link)

[2023.06.21] Yooeun Kim (presentation link) Keyword: Multimodal, single cell, multi-task learning
• Explainable multi-task learning for multi-modality biological data analysis , Nature Communications, 14 (2023) (link)

[2023.06.28] Kyeonghun Jeong (presentation link) Keyword: Spatial transcriptomics, single cell transcriptomics, VAE, multiomics
• Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk. Nature Communications , 13 (2022) (link)

[2023.06.28] Hoeyoung Kim (presentation link) Keyword: Gene annotation, Pangenome analysis, Alternative splicing, splicegraph
• Prokka: rapid prokaryotic genome annotation, Bioinformatics,  30 (14) (2014) (link)
• Roary: rapid large-scale prokaryote pan genome analysis, Bioinformatics,  31 (22) (2015) (link)
• RNA splicing analysis using heterogeneous and large RNA-seq datasets, Nature Communications,  14 (2023) (link)

[2023.07.17] Sunah Yang (presentation link) Keyword: exosome, biomarker
• Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers, Nature Communications 14 (2023) (link)
• Quantitative proteomics identifies the core proteome of exosomes with syntenin-1 as the highest abundant protein and a putative universal biomarker, Nature Cell Biology 23 (2021) (link)

[2023.07.17] Hongseok Ha(presentation link) Keyword: picoMeRIP-seq,  RNA editing
•Single-cell m6A mapping in vivo using picoMeRIP–seq, Nature Biotechnology  40 (2023) (link)
•RNA editing underlies genetic risk of common inflammatory diseases, Nature  608 (2022) (link)

[2023.08.02] Suwan Yu (presentation link) Keyword: TCRseq, single cell, AE
•LRT: Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity, PLOS Computational Biology  19 (7) (2023) (link)
•Autoencoder Model for Translating Omics Signatures, preprint  (2023) (link)

[2023.08.11] Ari Hong(presentation link) Keyword: subcellular localization, RNA stability
• mRNA stability and m6A are major determinants of subcellular mRNA localization in neurons, Molecullar Cell  83(15) (2023) (link)

[2023.08.11] Jaemin Jeon (presentation link) Keyword: Open set recognition
• Progressive Open Space Expansion for Open-Set Model Attribution,Computer Vision Pattern Recognition  (2023) (link)

[2023.08.16] Yooeun Kim (presentation link) Keyword: CCI, GRN, spatial transcriptomics, GNN
• CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics, Bioinformatics, 39 (2023) (link)

[2023.08.16] Sunah Yang (presentation link) Keyword: self-supervised represenation learning,  spatial -seq
• Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST,Nature Communications 14 (2023) (link)

[2023.08.23] Hongseok Ha(presentation link) Keyword: CAR-T, scRNAseq, immunology
•Single-cell antigen-specific landscape of CAR T infusion product identifies determinants of CD19-positive relapse in patients with ALL, Science Advances  8(23) (2022) (link)

[2023.08.23] SeungHo Han(presentation link) Keyword: scRNAseq
•Current best practices in single-cell RNA-seq analysis: a tutorial, Molecular SystemBiology  15(6) (2019) (link)

[2023.08.30] Hoeyoung Kim (presentation link) Keyword: long-read  RNAseq, transcript structure diverstiy, transcript annotation
• The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity, preprint (2023) (link)

[2023.09.07] Suwan Yu (presentation link) Keyword: Multi-omics, single cell RNA-seq, TCR-seq, Contrastive Learning
•Unified cross-modality integration and analysis of T-cell receptors and T-cell transcriptomes, preprint  (2023) (link)

[2023.09.21] Kyeonghun Jeong (presentation link) Keyword: single cell transcriptomics
•scVAE: variational auto-encoders for single-cell gene expression data Bioinformatics, 36 (16) (2020) (link)
•Single-cell RNA-seq denoising using a deep count autoencoder  Nature communications, 10 (2019) (link)

[2023.10.05] Jaemin Jeon (presentation link) Keyword: MIL, WSI
•Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks, 65 Medical Image Analysis  (2020) (link)

[2023.10.12] Ari Hong(presentation link) Keyword: uORF, translation, RNA secondary structure
•Pervasive downstream RNA hairpins dynamically dictate start-codon selection, Nature 621 (2023) (link)

[2023.11.02] Yooeun Kim(presentation link)  Keyword: GNN, Hypergraph, Single-cell multi-omics, GRN
• HGNN+: General Hypergraph Neural Network, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (3)(2023) (link)
• Gene regulatory network inference in the era of single-cell multi-omics, Nature Reviews Genetics, 24 (2023) (link) 

[2023.11.09] Sunah Yang (presentation link) Keyword: biological aging
•OMICmAge : An integrative multi-omics approach to quantity biological age with electronic medical records, preprint (2023) (link)

[2023.11.23] Hongseok Ha(presentation link) Keyword: circularRNA
•Accurate quantification of circular RNAs identifies extensive circular isoform switching events, Nature Communications 11, 90(2020) (link)

[2023.11.30] SeungHo Han(presentation link) Keyword: pangenome
•A draft human pangenome reference, Nature  617 (2023) (link)

[2023.09.21] Kyeonghun Jeong (presentation link) Keyword: single cell transcriptomics
•ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq  Bioinformatics, 39 (8) (2023) (link)