| A. Omics Data Integration & Analysis |
| A1 |
Chromosome rearrangement and genome complexity in hexaploid Hibiscus syriacus: Insights from pseudochromosome assembly and comparative analysis |
Hyunjin Koo |
|
| A2 |
Analysis of Myocarditis following mRNA COVID-19 Vaccination at Single-cell Level: Integating scRNA-seq and scATAC-seq |
Kim seulgi |
|
| A3 |
Systematic Omics Analysis of Large-scale Cancer Cell Lines Identifies CCR6 as a Potent Therapeutic Target to Combat Cancer Resistance to EGFR Inhibitors |
Eun-Ji Kwon |
|
| A4 |
Profiling of COVID-19 Patients Reveals Key Factors in the Path to Recovery |
Hye Seong |
|
| A5 |
Construction of mouse immune lncRNA atlas from various mouse cell types |
HyunSeok Song |
|
| A6 |
Integrative Analysis of Bulk RNAseq and single cell RNAseq revealed distinct cell types associated with Ulcerative Colitis |
Saqib Jahanzeb |
|
| A7 |
Comparative RNA-seq Analysis Utilizing Large-Scale Control Datasets in Oryza
sativa. |
ILSAN JEONG |
|
| A8 |
Site-specific transcriptomic analysis reveals novel insights into pterygium pathogenesis |
Hanseul Cho |
|
| A9 |
Identifying Causal Genetic Mechanisms of Asthma via an Integrative Analysis of Transcriptome- and Proteome-wide Association Studies |
Yubin Lee |
|
| A10 |
Identifying the Susceptibility Genes of Male-pattern Baldness with Transcriptome-wide Association Study |
Eunyoung Choi |
|
| A11 |
Characterizing feature selection for single-cell expression analysis |
Bukyung Baik |
|
| A12 |
Transcriptome analysis towards uncovering transcriptional reprogramming during callus formation in soybean |
Joo-Seok Park |
|
| A13 |
Spatial Transcriptomics Analysis of Mouse Spleen Tissue Seq-scope Data Using SSAM |
Dohyun Hwang |
|
| A14 |
Pseudo-temporal analysis of ribonucleoprotein complex assembly using proximity labeling and nanopore sequencing |
Heeseung Yoo |
|
| A15 |
A Simple Method for Analysis of the Heritability with Plant Chloroplast Genome |
Dong Su Yu |
|
| A16 |
HiCAN update: a reference-based estimation of the interaction between nuclear bodies and chromosomes |
Jaegeon Joo |
|
| A17 |
Development of a Deep Learning-Based Prediction Model for Metabolic Syndrome using genomic data |
Mira Park |
|
| A18 |
Hierarchical Structural Component Analysis of Biological Pathways using Graph Attention Network (HisCoM-GAT) |
Taewan Goo |
|
| A19 |
Unveiling Transcription Factors Driving Astrocyte Functional Development by Integrated Analysis |
Seongwan Park |
|
| A20 |
Shared and distinct mechanisms of MAZ, CTCF, and cohesin in mediating the interplay between chromosomes and nuclear bodies |
Sang Hyun Lee |
|
| A21 |
Q-omics: smart software for assisting oncology and cancer research |
Soyeong Kim |
|
| B. Cancer Genomics |
| B1 |
IFN-γ–related transcriptome profile as favorable prognostic factors in high-grade serous ovarian cancer |
Dae-Won Sim |
|
| B2 |
Improved liquid biopsy assay performance using sequencing by binding (SBB) |
Yeeun Shim |
|
| B3 |
Somatic Driver Gene Alterations are Associated with Predictive Anticancer Response and Prognostic Assessment in Pancreatic Ductal Adenocarcinoma |
Eunwoo Choi |
|
| B4 |
Cellular abundance-based prognostic model associated with deregulated gene expression of leukemic stem cells in acute myeloid leukemia |
Dong-Jin Han |
|
| B5 |
Indel mutational signatures reveal distinct subtypes of microsatellite instability |
Sunmin Kim |
|
| B6 |
Immunological subtyping of salivary gland cancer identifies histological origin-specific tumor immune microenvironment |
Jiyun Hong |
|
| B7 |
Mutational landscape analysis of prostate tumor |
Jihyun Kim |
|
| B8 |
Identification of proteogenomic landscape of whole genome doubling reveals putative therapeutic targets in each cancer type |
Eunhyong Chang |
|
| B9 |
Reversion of pathogenic BRCA1 L1780P mutation confers resistance to PARP and ATM inhibitor in breast cancer |
Se-Young Jo |
|
| B10 |
Conventional genomic predictive markers to immune checkpoint inhibitors are deteriorated in metastatic clear cell renal cell carcinoma |
Ahyeon Kim |
|
| B11 |
Development of large-scale structural variation detection software in Hi-C and single-cell Hi-C using few-shot learning |
Kyukwang Kim |
|
| B12 |
Molecular characterization of ovarian carcinoma by the size of somatic copy number alteration |
Doo Hyun Koh |
|
| B13 |
The aberrant expression of ISWI regulatory subunit RSF1 induces oncogenic reorganization of 3D genome that leads DNA repair defect |
Sunwoo Min |
|
| B14 |
New Druggable Targets in ETS rearrangement-negative CRPC |
Ju Young Lee |
|
| B15 |
Trajectory of lymph node metastasis characterizes molecular features of esophageal squamous cell carcinoma |
Jiho Park |
|
| B16 |
Development of an algorithm to evaluate 3D protein structure prediction similarities due to mutations |
Jongkeun Park |
|
| B17 |
Identification of niche-specific gene signatures between malignant and tumor microenvironments by integrating single cell and spatial transcriptomics data |
Saqib Jahanzeb |
|
| B18 |
Identifying biomarkers for predicting the response of MSC11FCD therapy to recurrent glioblastoma patients |
Ju-Won Kim |
|
| C. Metagenomics & Algorithms for Microbiomes |
| C1 |
Systematic Evaluation of Data Processing Pipelines and Machine Learning Classifiers for Shotgun Metagenomics-based Diagnosis of Crohn’s Disease and Colorectal Cancer |
Sungho Lee |
|
| C2 |
Gut microbiome modulation by colon surgery |
Sehun Ahn |
|
| C3 |
Exploring microbiome in gastric cancer microenvironment: a novel diagnostic strategy |
Mun Seong Ik |
|
| C4 |
Human reference oral virome |
Hanjune Kim |
|
| C5 |
Metagenome-guided machine learning unravels dynamic interactions of sulfate-reducing microbiomes with operational parameters in a full-scale wastewater treatment plant |
jeon eunsu |
|
| C6 |
Petasearch: Efficient and Sensitive Sequence Comparison at Scale |
Milot Mirdita |
|
| C7 |
MRGM: Mouse reference gut microbiome enabling comprehensive comparison of gut microbiome between mouse and human |
Nayeon |
|
| C8 |
Diagnosis of ocular infection using Nanopore Metagenomic sequencing |
Dongwoo Park |
|
| C9 |
De novo assembly of MAGs revealed prevalent anti-microbial resistant microbial strains among human community and their impact in individual microbiome |
Jae-Woo Baek |
|
| C10 |
HRGM v2: A global and high-quality human gut microbiome catalog of 155,211 near-complete reference genomes from 41 countries |
Junyeong Ma |
|
| C11 |
Association between newborn infant microbiota and parental skin disease |
JongHeon Park |
|
| C12 |
Microbial Risk Score for disease prediction using amplicon or shotgun metagenomic sequences |
Boram Kim |
|
| C13 |
Identifying biomarkers associated with type 2 diabetes using longitudinal microbiome data |
MD MOZAFFAR HOSAIN |
|
| C14 |
Student researcher |
Seungrin Yang |
|
| C15 |
Metabank for Metagenome Repository |
Suvin Baek |
|
| C16 |
Construction of comprehensive human oral microbiome catalog reveals characteristics of underestimated clades |
Jun Hyung Cha |
|
| D. Sequence Analysis |
| D1 |
Leveraging advances in natural language processing to decipher antibody
sequence |
Eunna Huh |
|
| D2 |
Bioinformatic analysis of zika virus miRNAs interacting with host genes |
Yoon Jung Kim |
|
| D3 |
Comprehensive analysis of synonymous codon usage in human Coxsackievirus B3 |
Xianglan Min |
|
| D4 |
Assembly of the complete mitochondrial genome of Pepper Cultivars (Capsicum annuum L.) |
Junseong Bae |
|
| D5 |
Analysis of airway microbiome related to particulate matter in patients with chronic obstructive pulmonary disease |
Sun |
|
| D6 |
Continuous wavelet transforms of nucleotide sequences simplify repeated regions in the genome |
Hyunsu Lim |
|
| D7 |
Intron analysis of the role of splicing event of Ulp2, a yeast enzyme responsible for yeast SUMO processing |
Seungji Choi |
|
| D8 |
Effects of hypoxia for chromatin accessibility during oncogene induced senescence |
Yoon Insoo |
|
| D9 |
Confident identification of co-fragmented peptides from unrestrictive modification search using machine learning |
Sunjin Park |
|
| D10 |
Noncoding Rare Variant Association in Alzheimer's Disease Using Single-cell Chromatin Accessibility Data |
Chanhee Kim |
|
| D11 |
Comparative transcriptome analysis of periodontitis and peri-implantitis in human subjects |
Yeongjoo Kim |
|
| D12 |
MOSCAL: Detection of mosaic variants using linked-read sequencing |
YONGJUN KIM |
|
| E. Genomic Variation & Disease |
| E1 |
Dysregulation of the Wnt/β-catenin signaling pathway via Rnf146 upregulation in a VPA-induced mouse model of autism spectrum disorder |
Seoyeon Kim |
|
| E2 |
Prevalence and Characterization of NOTCH2NLC GGC Repeat Expansions in Koreans: From a Hospital Cohort Analysis to a Population-Wide Study |
Juhyeon Hong |
|
| E3 |
Identification of Novel Genetic Variants in Pulmonary Arterial Hypertension through Whole Exome Sequencing in a Korean Population |
Moonyoung Lee |
|
| E4 |
Oligogenic contribution of rare variants for autism spectrum disorder |
Hyeji Lee |
|
| E5 |
Role of FRZB in proliferative vascular diseases |
Hyomin Kim |
|
| E6 |
Identify Cryptic genetic background under Thyroiditis from ICI treatments using Whole Genome Sequencing |
Hojin Lee |
|
| E7 |
Multivariate Analysis of identifying novel genetic variants for Metabolic Syndrome in Korean Cohorts |
Dasom Kim |
|
| E8 |
Epigenetic footprints of industrial hazards: discovering methylation markers and their disease associations. |
Hyeon Gyu Shin |
|
| E9 |
Transcriptome-Wide Association Studies of 81 traits in 79,294 individuals from Korean Populations |
Min Heo |
|
| E10 |
Whole-Genome Sequencing Improves the Diagnostic Yield of Idiopathic Dilated Cardiomyopathy |
Seunghee Moon |
|
| E11 |
Whole exome sequencing and familial segregation study with targeted sequencing revealed pathogenic genes in inherited cystic kidney disease |
Dajun Lee |
|
| E12 |
Whole genome sequencing analysis identifies sex differences of familial risk contributing to phenotypic patterns in autism spectrum disorder |
Soo-Whee Kim |
|
| E13 |
Predicting Contribution of Genome-Wide Noncoding Mutations Disrupting Cell Type-Specific Regulatory Elements to Autism Risk Using CWAS-Plus |
In Gyeong Koh |
|
| E14 |
CWAS-Plus: Estimating genome-wide association of noncoding variation from whole genome sequencing data |
Yujin Kim |
|
| E15 |
Assessing adult neurogenesis activity and validating association to Alzheimer’s disease |
SEUNGSEOK KANG |
|
| E16 |
A Method of Identifying False Positives in the Variant Calling |
Sunhee Kim |
|
| E17 |
Association of genetic variants with pre-diabetes and type 2 diabetes using illness-death model in Korean adults |
Oh jeongmin |
|
| E18 |
Germline indel calling performance is highly associated with indel property and parameter optimization |
Mooyoung Kim |
|
| E19 |
Cardiovascular Polygenic Risk Scores and Mortality Risk in COVID-19 Patients |
Jun Sik Kim |
|
| E20 |
Investigating the role of polygenic risk scores for comorbidities in COVID-19 susceptibility |
Soo Min Song |
|
| E21 |
Comprehensive benchmarking of variant calling on X chromosome from large-scale whole genome sequencing data |
Gang-Hee Lee |
|
| F. Pharmacogenomics |
| F1 |
Advancements in DILI Prediction Models |
Chanhee Lee |
|
| F2 |
Utilizing Mendelian Randomization to Investigate the Therapeutic Efficacy of Drugs Associated with Androgenetic Alopecia with DEEPCT |
Su Han Cho |
|
| F3 |
Pharmacogenomic Analysis of Korean Patients with Cognitive Impairment and Dementia |
SooYeon Park |
|
| F4 |
Elucidation of novel therapeutic targets in melanoma influencing mitochondrial biogenesis via STAT6 |
Soo Youn Lee |
|
| F5 |
Transcriptome-based systematic analysis of the molecular mechanisms of Bojungikki-Tang on immune cell networks |
sang yun kim |
|
| F6 |
Unraveling the Protective Mechanisms of Jakyak-gamcho-tang's Phytochemicals Against Muscle Atrophy |
Heerim Yeo |
|
| G. Phylogenetics |
| G1 |
Determining the full sequence of the chloroplast genome of Wolffia arrhiza (Lemnoideae) and analyzing its evolution to other members of the Araceae family |
Park Halim |
|
| G2 |
Genetic diversity-based design of Nipah virus Fusion protein vaccines candidate sequences in Malaysia, Bangladesh, and India. |
Min Su Yim |
|
| G3 |
Characterization of Bioleaching Efficiency by Acidophilic Iron Oxidizing Bacteria isolated from Abandoned Mining Area in South Korea |
Hyo Jung Lee |
|
| G4 |
Exploring Marmosets: Evaluation of Model Animals in Disease Systems and Drug Systems |
Jeawoon Ryu |
|
| H. Single Cell Sequencing |
| H1 |
Characterization of altered molecular mechanisms in Parkinson’s disease
through cell type–resolved multiomics analyses |
Andrew J. Lee |
|
| H2 |
Epigenetic Landscape of Adipocytes in T2DM: A Single-Cell Analysis Using sn-m3C-seq |
Chanho Park |
|
| H3 |
Gene regulatory network analysis on snRNAseq revealed key regulators for hepatocellular carcinoma progression |
Taehong Min |
|
| H4 |
Revealing Cell Type-Specific Transcriptional Signatures of Hippocampal Circuit in Fear Memory Network |
Jungeun Ji |
|
| H5 |
Analysis of various ion channel transcripts in CD4+ T cell subsets using single-cell RNA sequencing. |
Sujin Park |
|
| H6 |
Characterization of a novel epithelial cell type in sinonasal cavity and its potential disarray in patients having both upper and lower respiratory tract diseases |
Juhyun Kim |
|
| H7 |
Single-cell analysis of multiple cancers in the upper gastrointestinal tract uncovers immune characteristics of tumor microenvironments linked to the predictive biomarkers for immunotherapy |
Seungbyn Baek |
|
| H8 |
|
|
|
| H9 |
Unveiling resistance mechanisms of non-small cell lung cancer against
third-generation EGFR tyrosine-kinase inhibitors through
single-cell DNA sequencing |
Seungho Oh |
|
| H10 |
Spatial arrangement of disease-associated molecular signatures in the neurodegenerative human brain at single-cell resolution |
SE YOUNG JIN |
|
| H11 |
CD161+ TRM cells counteract HPV-associated clinical benefits in oropharyngeal cancer immunotherapy |
Junha Cha |
|
| H12 |
Comparative analysis of papillary and anaplastic thyroid cancer using single-cell transcriptomics |
Kwangmin Yoo |
|
| H13 |
Integrative analyses of single-nucleus and spatial transcriptome resolve neurodegenerative molecular ecosystem in the human brain |
Baekgyu Choi |
|
| H14 |
Human cell-type-specific network atlas (hcNETLAS) for connecting links from genes to cells to diseases |
Jiwon Yu |
|
| H15 |
Single-cell profiling unveils molecular insights and region-specific heterogeneity in the hippocampus during global ischemia |
Donghee Kwak |
|
| H16 |
Single-cell analysis reveals dysregulation of the immune system linked to poor prognosis in Fusobacterium nucleatum-infected colorectal cancer |
Ilseok Choi |
|
| H17 |
Ionizing radiation inhibits hatching of zebrafish embryo by inducing tissue inhibitors of metalloproteinases in transcriptional level |
Eun Jung Kwon |
|
| I. Protein / RNA Analysis, Structure, and Dynamics |
| I1 |
A comparative analysis of mRNA codon optimization methods |
Sangheon Lee |
|
| I2 |
Characterization of defense immune protein for Feline Infectious Peritonitis Virus (FIPV) |
Kyoungmin Lee |
|
| I3 |
Widespread 8-oxoguanine modifications of miRNA seeds differentially regulate redox-dependent liver cancer development |
Jongyeun Park |
|
| I4 |
Petabase-scale Homology Search for Structure Prediction |
Sewon Lee |
|
| I5 |
Reweighted ensemble structures of Aβ42 monomer using maximum entropy approach |
juhyeong jeon |
|
| I6 |
Machine Learning Approach for Understanding the Effect of CD33 and TREM2 in Alzheimer's Disease |
Jisu Jeong |
|
| I7 |
Single-molecule analysis on the interaction between translation, poly(A) tail, and diverse sequence context |
Seungbeom Han |
|
| I8 |
Alternative Splicing of RPS24 Plays a Role in Cancer Development and Progression |
JIYEON PARK |
|
| I9 |
Coevolution analysis of Intrinsically Disordered Proteins for characterizing complex functionalities |
Joongyu Heo |
|
| J. Computational Drug Discovery |
| J1 |
B cell epitope prediction using graph attention network and ESM-based pretrained protein model embeddings |
Sungjin Choi |
|
| J2 |
BEAR: a novel virtual screening method based on large-scale bioactivity data |
Wankyu Kim |
|
| J3 |
Molecular Modeling Approaches to Discover Novel PTP1B Inhibitors for Treatment of Type 2 Diabetes Therapy |
Yoon Sanghwa |
|
| J4 |
AMP-BERT: Prediction of antimicrobial peptide function based on a BERT model |
Hansol Lee |
|
| J5 |
Enhancing drug response prediction and interpretability through gene ontology and drug target information integration |
Yeojin Shin |
|
| J6 |
A Novel Framework for Drug Approval Prediction using Chemical Structure with Knowledge Distillation |
Changyun Cho |
|
| J7 |
Computer-aided screening for potential GSK-3β inhibitors: a combination of pharmacophore modeling, molecular docking simulation approaches |
Ju young Cho |
|
| J8 |
Graph Convolutional Network Model based on Drug-gene-disease Network for Drug Repurposing |
Jiwon Seo |
|
| J9 |
FragGNN: Enhancing Molecular Property Prediction through Fragment-based Hierarchical Graph Neural Networks |
Dohyeon Kim |
|
| J10 |
Computational Strategies for Discovering Positive Allosteric Modulators for A1AR Using Pharmacophore Modeling and Molecular Dynamics Insights |
Bilal |
|
| J11 |
Ensemble Models of Tensor Decomposition and Multi-layer Perceptron for Drug Repositioning |
Jong-Hoon, Park |
|
| J12 |
The Dr.Emb Appyter: A Web Platform for Drug Discovery using Embedding Vectors |
Songhyeon Kim |
|
| J13 |
BayeshERG: A Robust, Reliable, and Interpretable Deep Learning Model for Predicting hERG Channel Blockers |
Hyunho Kim |
|
| J14 |
Predicting optimal natural compounds that modulate multi-targets for type 2 diabetes mellitus-related complications |
Hee Yang |
|
| J15 |
Integration of multiple AI frameworks and data representations for
enhancing the performance of predicting blood-brain barrier permeability |
Erkhembayar Jadamba |
|
| J16 |
Evaluating BERT-based large language models in target druggability
prediction |
Sera Park |
|
| J17 |
An implementation of intelligent platform to identify new ADC targets |
Dae Sun Chung |
|
| J18 |
Transcriptome-based identification of drug mechanisms (KMAP Express_Education) |
Wankyu Kim |
|
| K. ML and AI in Medicine and Healthcare |
| K1 |
LOGICS: Learning optimal generative distribution for designing de novo chemical structures |
Bongsung Bae |
|
| K2 |
Identifying microRNAs associated with tumor immunotherapy response using an interpretable machine learning model |
Dong-Yeon Nam |
|
| K3 |
User-friendly automated analysis for diagnosis of repeat expansion disorders using targeted nanopore sequencing |
Yoojung Han |
|
| K4 |
AI-based Design of Augmented 5’UTR with a High Translational Efficiency |
Solbeen Kim |
|
| K5 |
Multi-task learning with modeling gene interaction using transformer for predicting patient outcomes |
Bonil Koo |
|
| K6 |
Multi-Task Aware Learnable Prototypes on Few Shot learning for Molecular Property Prediction |
Sangseon Lee |
|
| K7 |
Leveraging Computational Chemical-Induced Transcriptomic Cell State for Drug Response Prediction Through Transfer Learning |
Dongmin Bang |
|
| K8 |
Improving Out-of-Distribution Generalizations in Molecule Graphs with Hierarchical Semantic Environments |
Yinhua Piao |
|
| K9 |
Exploring ligand-receptor pairs associated to cancer immunotherapy responses using machine learning |
LeeHyunJi |
|
| K10 |
Predicting adverse drug reaction signal from medical data via systematic data preprocessing and machine learning |
Junhyeok Jeon |
|
| K11 |
Sequence-based prediction of anti-CRISPR proteins using transformer model |
Chan-Seok Jeong |
|
| K12 |
Multi-Channel Convolutional Neural Network Models for Personalized Anti-Epileptic Drug Suggestion Using Medical History |
Daeahn Cho |
|
| K13 |
Deconvolution of transcriptomic changes caused by drug multi-target perturbation using matrix factorization |
Jieun Sung |
|
| K14 |
DNA Sequence-Based Virus Classification Using Deep Learning and Machine Learning |
Kavya Dasaramoole Prakash |
|
| K15 |
AMPs-GCN: Classification of antimicrobial peptide activites based on graph convolutional network |
Young-Tae Won |
|
| K16 |
Between Rules and Virtues: Sentiment Insights into AI’s Ethical Landscape in Healthcare |
Kim Rubiga |
|
| K17 |
BlazePose-Assisted Frontal Gait Video Analysis: An Efficient Alternative for Biomechanical Assessment and Early Disease Detection |
Sung Hoon Choi |
|
| K18 |
Exploratory data analysis for predicting anticancer drug reactivity and mechanism of action |
Hanna Jeon |
|
| K19 |
Interpretation of anticancer drug action using predicted features obtained from machine learning |
YUSEONG KWON |
|
| K20 |
Omics-based drug response prediction via machine learning methods |
Min-Ju Kim |
|
| K21 |
Confidence Estimation of a Clinical Decision Support System for Determining the Colonoscopy-Surveillance Interval |
Nayeon Kim |
|
| K22 |
The Effectiveness of Transfer Learning in Predictive Modeling for Pediatric Cancers: Insights from VAECox Architecture |
Taewon Kim |
|
| K23 |
Development of Data/Model-based Ensemble Machine Learning Model for Prediction of Sepsis Severity Using Sepsis Genomic Synthetic Data |
Sooyoung Jang |
|
| K24 |
Sepsis diagnosis through cellular morphology with biological insights and interpretations |
Jong Hyun Kim |
|
| K25 |
Prediction of Alzheimer’s disease using AI model based on SNP chip data |
Myeongji Cho |
|
| K26 |
Developing Prompts from Large Language Model for Extracting Clinical Information from Pathology and Ultrasound Reports in Breast Cancer |
Bum-Sup Jang |
|
| K27 |
COVID-19 severity risk prediction with machine learning approaches |
Hye-Yeong Jo |
|
| K28 |
Estimation of immune cell type composition from microRNA expression data |
Seo-Young Park |
|
| L. etc |
| L1 |
SoyPedi: A breeder-friendly database for soybean cultivars based on phenotype-pedigree mapping information |
Min-Gyun Jeong |
|
| L2 |
Chromosome-Centric Human Proteome Report of Chromosome 11 Team |
Park MiNa |
|
| L3 |
CodeRbook: R package for Interactive Exploratory data analysis and for data checks to build metadata |
BYUNGJU KIM |
|
| L4 |
Characterization Services for Biopharmaceutical-producing Cell Line in Compliance with ICH Q5 |
JooYeon Lee |
|
| L5 |
A new strategy for glycopeptide enrichment using combining ZIC-HILIC and molecular weight cut-off filter |
KANG JI HYUN |
|
| L6 |
DNA-based MSA Transformer: Advancing DNA Feature Prediction |
Sukhwan Park |
|
| L7 |
Single Cell Data Analysis using Hierarchical Clustering Based on PCA with Fuzzy C-Means |
VIKAS SINGH |
|
| L8 |
CAFA-Powered Insights: Predicting Protein Function in the Post-Genomic Era |
Kim Rubiga |
|
| L9 |
STK6: a novel therapeutic target for incurable breast cancers |
Sung Baek Jeong |
|
| L10 |
NovoCert: Statistical validation of de novo peptide sequencing results |
ZHANG SHANJI |
|
| L11 |
Identification of genetic loci associated with skin aging traits in a large Korean population |
Joong-Gon Shin |
|
| L12 |
Nuclear transcription factor STAT6 regulates mitochondrial biogenesis through decrease of mitoribosome assembly factor MTG1. |
Hyunmi Kim |
|
| L13 |
Identification of microRNA regulating simultaneously gene expression associated with intramuscular fat deposition in Korean Native Cattle |
Jiyeon Lee |
|
| L14 |
An artificial intelligence tool to evaluate properties of SARS-CoV-2 mutations |
Do Young Seong |
|
| L15 |
An Implementation of Proactive Strategies for Clinical Genome and Transcriptome Data Utilization |
hyojeong park |
|
| L16 |
Algorithm Development for Analysis of O-GlcNAcylated Protein using LC-MS/MS |
DASOM AN |
|
| M. Systems Biology |
| M1 |
Understanding the molecular mechanisms of muscle atrophy: A single-nucleus
transcriptome analysis of mice with dexamethasone-induced skeletal muscle atrophy |
Bumsuk Kim |
|
| M2 |
Generative model based on 3D molecule structure driven Atom-pair map |
Gina Ryu |
|
| M3 |
Investigating THBS1 for Overcoming Radioresistance in Head and Neck Squamous Cell Carcinoma (HNSCC) : Transcriptomic Insights and Drug Prediction |
Minji An |
|
| M4 |
Targeting Metabolic Genes in Drug-Resistant Breast Cancer Cells to Improve Their Drug Response by Using Genome-Scale Metabolic Models |
Hae Deok Jung |
|
| M5 |
Uncovering molecular mechanisms of muscle atrophy caused by different
factors through a comprehensive transcriptome analysis |
Hanbi Lee |
|
| M6 |
Identification of therapeutic targets for muscle atrophy via analyzing
transcriptomic profiles with systems biology |
Ahyoung Choi |
|
| M7 |
Leveraging Molecular Signature Tile Model (MSTM) and Multi-Modal Data for Advancing Personalized Cancer Care on Mobile Platforms |
Jeong Jeong |
|
| M8 |
Determining Bone Formation Metabolic Pathway Activity in the TgA86 Mouse Model of Spondyloarthritis through RNA-Seq Data Analysis |
Sanghyeon Yu |
|
| M9 |
Transcriptional and Metabolomic Changes in Primary Open-Angle Glaucoma |
Jisu Jeong |
|
| M10 |
Utilizing Systems Biology Methods to Explore the Effectiveness of Autoimmune Disease Medications in COVID-19 Patients |
Yoo Jin Sung |
|
| M11 |
The improved method to infer global gene regulatory network for investigating disease genes using High-Performance Computing resources |
Younghoon Kim |
|
| M12 |
Transcriptome-based clustering and analysis of NASH patient models reveals cluster-specific signatures and underlying disease mechanisms |
Gina Ryu |
|
| N. Biological Networks & Integrative Analysis |
| N1 |
Profiling of changes in gene expression associated with epigenetic changes in peripheral blood cells under hyperinsulinemic euglycemic clamp condition |
Minjae Joo |
|
| N2 |
TENET+: a tool for reconstructing gene networks by integrating single cell expression and chromatin accessibility data |
Hyeonkyu Kim |
|
| N3 |
Pan-cancer single epithelial cell analysis identified specific and common regulatory features of various cancers. |
Jaewoo Mo |
|
| N4 |
Synthetic lethality prediction via attentive knowledge graph neural network in the divergent human cancer cell-lines |
Songyeon Lee |
|
| N5 |
Validation of Network-Based Algorithm through Prediction of Drug Efficacy in Type 2 Diabetes |
Jiyeon Kim |
|
| N6 |
Improvement of human interactome with de novo network inference from single-cell atlas |
EuiJeong Sung |
|
| N7 |
MIMR: A web tool for integrated analysis of miRNA and mRNA using Random Walk with Restart |
kim dayeon |
|
| N8 |
Leveraging genetic effects in thyroid dysfunctions via cell type-specific network propagation |
Jaeseung Song |
|
| N9 |
Transcriptomic changes fatty liver in aging |
Kyuwon Son |
|
| N10 |
Glutamine-Independent Survival Mechanisms in Colorectal Cancer Cells: An Integrative RNA-seq, ATAC-seq, and miRNA-seq Study |
Ji-Yeon Lee |
|
| N11 |
|
|
|
| O. Public Health & Population Health Informatic |
| O1 |
Interactive web-based dashboard for examining the spatial and temporal dynamics of COVID-19 in South Korea |
Hanbyul Song |
|
| O2 |
Latent class growth analysis of COVID-19 pneumonia patients with longitudinal radiologic data for predicting severity and prognosis |
Seo Yeonju |
|
| O3 |
PhD student |
Kyulhee Han |
|
| O4 |
Discovering environment-based disease similarity network using NHANES datasets |
Younghoon Kim |
|
| P. Imaging Informatics |
| P1 |
subtyping of mild cognitive impairment using machine learning model based on multimodal neuroimaging data |
HyeRyeong Nam |
|
| P2 |
Development of Novel Video-based method for Epileptic Seizure Detection in Mice |
junaid khan |
|
| Q. Large language model (LLM) for healthcare applications |
| Q1 |
Developing Prompts from Large Language Model for Extracting Clinical Information from Pathological and Ultrasound Findings in Breast Cancer |
Bum-Sup Jang |
|
| R. Data Integration, Harmonization, and Ontology |
| R1 |
Virus Classification using Knowledge Graph |
Mikyung Je |
|
| R2 |
Advancements and prospects of PubCaseFinder, a generic name for three services related to rare and genetic diseases |
Jae-moon Shin |
|
| S. Multimodality modeling |
| S1 |
Gene expression Modeling for synthetic biology |
HongYeon Kim |
|
| T. Computational Phenotyping |
| T1 |
Sequence-based Prediction of Bacterial Essential Genes using Protein Language Models |
Seong-Bo Heo |
|