| A. Metagenomics & Algorithms for Microbiomes |
| A1 | Evaluating Metagenomics Fosmid Libraries Using Vector-Adjacent Sequences | Suvin Baek | |
| A2 | VertBert | JunHo Jung | |
| A3 | Comparative Genomic Analysis of Microbial Community Diversity in Soybeans Cultivated from Korea and Japan Soils | Marianne Yssabelle Sabdao Lunas | |
| A4 | Development of the Dog Reference Gut Microbiome (DRGM) Catalog to Address Sample and Diversity Bias in Dog Microbiome Research | Kim Yerin | |
| A5 | Optimizing Extraction Kits and Sequencing Techniques for Efficient Analysis of Cow Fecal Microbiome Diversity | Amanzhanova Amina | |
| A6 | Alteration of the gut microbiome driven by colon surgery | Sehun Ahn | |
| A7 | MRGM: A Comprehensive Catalog of Mouse Gut Microbial Genomes Expanding Taxonomic Diversity and Functional Insight | Nayeon Kim | |
| A8 | Metabuli App: A High-Performance, Accessible Platform for Metagenomic Taxonomic Profiling | SunJae Lee | |
| A9 | Comparative genomics applied to understand taxonomic relationship among Neisseria species | HyunJun Lee | |
| A10 | The catalog of near-complete genomes improves taxonomic and functional understanding of the human gut microbiome | Junyeong Ma | |
| A11 | Dysbiosis of the adolescent gut microbiota: implications for immune modulation in inflammatory bowel disorders and obesity | Minjae Joo | |
| A12 | A comprehensive genome catalog of the human oral microbiome expands our understanding of its phylogenetic diversity and clinical implications | Jun Hyung Cha | |
| A13 | A Snakemake-based bacterial whole genome comparison pipeline for multi-group clinical isolates | Hoeyoung Kim | |
| A14 | Comprehensive benchmarking study of metagenomic binning tools across diverse datasets | Jungyeon Kim | |
| A15 | HUMIPRO: A database of metagenomic profiles from over 30,000 gut, oral, and vaginal samples for the study of human microbiome | Geon Koh | |
| A16 | Metformin-induced alterations in gut microbiome compositions and antibiotic resistance genes | HanBin Kim | |
| A17 | Unique signatures of gut microbiome in non-alcoholic fatty liver disease | Wonjong Kim | |
| A18 | Human reference gut virome | Hanjune Kim | |
| A19 | Differences In Gastric Neoplasms Induced By Helicobacter and Non-Helicobacter Microbiomes | Youngjin Shin | |
| B. Multimodality modeling |
| B1 | PathCLAST: a Pathway-augmented Contrastive Learning with Attention mechanism for Enhanced Spatial Domain Identification in Spatial Transcriptomics Data | Minho Noh | |
| C. Single Cell Sequencing |
| C1 | Single-nucleus and spatial transcriptomic analysis identified molecular features of neuronal heterogeneity and distinct glial responses in Parkinson’s disease. | Hwisoo Choi | |
| C2 | Identification of Mechanisms Underlying Sex Determination and Differentiation Using Single-cell Multiome Analysis | Kim Jisoo | |
| C3 | Primate-specific microRNA evolved from non-canonical target recognition expands cortical interneuron reportoire | Jung Lee | |
| C4 | Predictive response and resistance factors of Duruvalumab and Tremelimumab neoadjuvant combination immunotherapy in head and neck cancer | Junha Cha | |
| C5 | CellCraft: a web-based platform for single cell analysis for reconstructing gene regulatory network | Dongmin Shin | |
| C6 | FastTENET: an accelerated TENET algorithm based on manycore computing in Python | Rakbin Sung | |
| C7 | Exploring controllability in Developmental TENET gene regulatory networks across species. | Jiyeon Park | |
| C8 | Single-cell RNA sequencing reveals the heterogeneity of adipose tissue-derived mesenchymal stem cells under chondrogenic induction | CHUN JEEWAN | |
| C9 | Dexamethasone-Induced Muscle Atrophy: A Comparative Single-cell Transcriptomic Analysis | Bum Suk Kim | |
| C10 | Exploring Neuronal and Astrocytic Dysregulation in Phelan-McDermid Syndrome Using Single-Cell Transcriptomics | Kim chae youn | |
| C11 | Deciphering Head and Neck Cancer Microenvironment: Single-cell and Spatial Transcriptomics Reveals Human Papillomavirus-Associated Differences | Hansong Lee | |
| C12 | Dysfunction of secretory IgA contributes to poor outcomes in Fusobacterium-infected colorectal cancer. | IlSeok Choi | |
| C13 | Enhancing Disease Prediction by augmenting the Human Interactome with Cell-Type-Specific Co-Expression Networks from Single-Cell Atlas Data | Euijeong Sung | |
| C14 | Chromatin accessibility analysis and architectural profiling of human kidneys reveal key cell types and a regulator of diabetic kidney disease | Donggun Kim | |
| C15 | A single-cell lncRNA atlas unveils cell type- and age-specific expression of lncRNAs across kidney cell types | Gyeong Dae Kim | |
| C16 | Bayesian Inference of Cell-Dependent RNA Velocity Using Variational Mixtures from Multi-Omic Data | Ari Hong | |
| C17 | Single-Cell RNA Sequencing Reveals Transcriptomic Heterogeneity of Lymphocytes in Ulcerative Colitis | Kyung Min Lim | |
| C18 | Identifying Key Transcription Factors in Chondrocyte Dedifferentiation by single-cell multiomic analyses | Sang Hyun Lee | |
| C19 | Differential beta-coronavirus infection dynamics in human bronchial epithelial organoids | Suhee Hwang | |
| C20 | Investigation of disease-associated spatial molecular signatures in the neurodegenerative human brain at single-cell resolution | Seyoung Jin | |
| C21 | Enhancing cell type classification in scRNA-seq data using Transformer based model and singular value decomposition | Sanghun Sel | |
| C22 | Exploring the genetic landscape of immune evasion in colorectal cancer using single cell transcriptome | Chanho Park | |
| C23 | Single-cell multi-omics analysis reveals factors in tumor microenvironment underlying poor immunotherapy responses in ALK-positive lung cancer | Seungbyn Baek | |
| C24 | Exploring the cellular and temporal specificity of neurological disorder genes in human brain development | Seoyeon Kim | |
| C25 | Defining Novel Ecotypes in Lymphoepithelioma-like Carcinoma of the Bladder through Spatial Transcriptomics | Hyung suk Kim | |
| C26 | Elucidate the Immune Mechanisms in Endometriosis through Analysis of Retrograde Menstrual Blood | Hyung suk Kim | |
| C27 | Identification of CAF-Derived Ligands inducing Tumor Progression in Colorectal Cancer | Je Bin Lee | |
| C28 | Brain Organoid Cell Type Prediction by Brain Single-cell Atlas Trained Annotation Models | Jihae Lee | |
| C29 | Brain single-cell transcriptomic atlas reveals neurodiversity and disease-specific glial cell types across regions and developmental stages | Koh In Gyeong | |
| D. Protein / RNA Analysis, Structure, and Dynamics |
| D1 | Deadenylation kinetics of mixed poly(A) tails at single-nucleotide resolution | juhyeon Kim | |
| D2 | Packaging signal of SARS-CoV-2 | Jongmin Lim | |
| D3 | High Accuracy Antibody-Antigen Complex Structure Prediction with Epitope Information | Kunhee Kim | |
| D4 | Generating MSA for Protein Structure Prediction via Structure Search and Sequence Design | Soohyun Jo | |
| D5 | Analysis of interactions between cytosol-penetrating antibody and cell membranes through MD simulation | Haelyn Kim | |
| D6 | Alignment-free Nucleic Acid Binding Site Prediction using Equivariant Graph Neural Network and ESM Embbedings | Joohyun Cho | |
| D7 | Comprehensive discovery of RNA modification sites in the human transcriptome | Hyeonseo Hwang | |
| D8 | Towards novel therapeutics against SARS-CoV-2 | HEE RYUNG CHANG | |
| D9 | Pseudo-temporal analysis of ribonucleoprotein complex assembly using proximity labeling and nanopore sequencing | Ku Jayoung | |
| D10 | Rapid and Sensitive Protein Complex Alignment with Foldseek-Multimer | Woosub Kim | |
| Public Health & Population Health Informatic |
| D11 | AlphaSS : Improving Protein Structure Prediction with Disulfide Bond Information | Sehoon Park | |
| E. Imaging Informatics |
| E1 | LadybirdMNIST: ladybird pattern dataset construction via PDE-based pattern generation and pattern classification | Seongmi Woo | |
| F. Large language model (LLM) for healthcare applications |
| F1 | MV-CLAM: Multi-View Molecular Interpretation with Cross-Modal Projection via Language Model | Sumin Ha | |
| F2 | Assessing GPT4’s capabilities for the synthetic EMR generation and diagnosis of rare diseases | Yoonbee Kim | |
| G. Pharmacogenomics |
| G1 | Investigating the shared and distinct mode of action of NSAIDs related to gastrointestinal side effects | Seoyoon Huh, Sungbeen Lee, Jaeseung Song, and Wonhee Jang | |
| G2 | GCNPath: Decoding Anticancer Drug Sensitivities with Pathway-based Graph Neural Networks | Hyeon Jun Yoon, and Minho Lee | |
| G3 | Synergistic Effect of Bojungikgi-tang with Immune Checkpoint Inhibitors: Transcriptomic Analysis of Patient Blood Samples | sang yun kim | |
| H. Phylogenetics |
| H1 | Comparative genomics of Wolffia species: Investigating genome size evolution and the functional implications | Yejin Lee | |
| I. Public Health & Population Health Informatic |
| I1 | A Visualization Tool for Brain Imaging Data from Multicenter Cohort Studies | Yun Inze, Myeongji Cho, Hye Ryeong Nam, Chang Hee Chu, Sang Cheol Kim | |
| J. Computational Phenotyping |
| J1 | Interpretable Predictions of Genetic Perturbation Transcriptional Outcomes with Multi-View Graph Learning | Yooeun Kim | |
| K. Genomic Variation & Disease |
| K1 | Near-optimal variant calling by pseudo-database construction | Hyeonjung Lee | |
| K2 | Stacking model as a method for genomic prediction | Sunhee Kim, Dongju Lee, Chang-Young Lee | |
| K3 | Differential impact of lifestyle habits on gout incidence based on genetic risk levels | Hyunjung Kim | |
| K4 | Genetic causal relationships between menarche, menopause age, and breast, ovarian, and endometrial cancers in East Asian women. | Hyunsong Koh | |
| K5 | Leveraging genetic effects in Grave's disease via cell type-specific network diffusion | Jaeseung Song | |
| K6 | Rapid precision diagnosis of repeat expansion disorders by Cas9-enrichment and long-read sequencing | Yoojung Han | |
| K7 | GVRP: Genome Variant Refinement Pipeline for Variant Analysis in Non-Human Primates Using Machine Learning | Kibeom Kim | |
| K8 | SVDP: Somatic Variation Detecting Pipeline Using PCA and Machine Learning | MinSu Kim | |
| L. Haplotypes & Population Genomics |
| L1 | PAPipe: A Pipeline for Comprehensive Population Genetic Analysis | Park Nayoung | |
| L2 | Mapping GWAS variants to endothelial differentiation gene regulatory program uncovers the significance of endothelial cells in complex human diseases | Gyeongsik Park | |
| M. Sequence Analysis |
| M1 | High-Fidelity Synthetic DNA Generation via GANs : Enhancing Genetic Regulation and Therapeutic Potential | Myeongryun Lee | |
| M2 | Prediction of DNA marker candidates for species identification using k-mer based Machine learning model | Chi-Hwan Kim | |
| M3 | Dsembler – DNA Assembly Designer: A Design tool for Facilitating Gene Assembly | Gyeongmin Park | |
| M4 | Enhancing Data Integrity in Genome-wide Pooled Screens: The Role of oveQC in Quality Control | Jihyeob Mun | |
| M5 | Unraveling the Impact of Long Terminal Repeats(LTRs) on clonal variation
in iPSC Differentiation Efficiency | JEONG SEUNGHEE | |
| M6 | Abasic CRISPR RNAs inherently harness fidelity of SpCas9 for genome editing | Geun-Woo D. Kim | |
| M7 | Comparative Analysis of Cuscuta Chloroplast Genomes for Developing Reliable Genetic Markers for Species Classification | KANG YANG JAE | |
| M8 | Nanopore Direct Sequencing of RNA-DNA Hybrid Molecules | Sojeong Lee | |
| M9 | Genome decoding of Pistia stratiotes (Water lettuce) and comparative genomics analysis to uncover water purification mechanisms | Park Halim | |
| M10 | Evaluating Plasma Cell-Free mRNA as a Biomarker for Early Detection of Aggressive Solid Tumors | Jimin Seo | |
| M11 | MRPrimerW3: an Expanded Tool for Rapid Design of Gene-Specific and Species-Specific Primers for PCR | Ji-an Oh | |
| N. Biological Networks & Integrative Analysis |
| N1 | PONYTA: Prioritization of phenotype-related genes from mouse KO events using PU learning on a biological network | Jun Hyeong Kim | |
| N2 | Integrated Machine Learning and Bioinformatics Analysis Reveal Hub Genes in Innate and Adaptive Immunity Linked to Autism Spectrum Disorder and Non-Typical Neurodevelopment from Prenatal Gene Expression Changes | Payam H. Kasani | |
| N3 | MoBC-Net: R-Package for Distance between Modules-of-Interest and Module-Betweenness Centrality of Key Bridge Nodes | Baek yoomi | |
| O. Computational Drug Discovery (1) |
| O1 | Drug Discovery with Multi-Task Learning Platform | Jisun Jung | |
| O2 | Discovery of Potential GSK-3β Inhibitors: a combination of Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation | Juyoung Cho | |
| O3 | Deep Learning Strategy for Predicting Interaction between Protein and Ligand | Sanghwa Yoon | |
| O4 | From the creation of new compounds using AI to the discovery of new drug candidate : Graph DF, Graph DTA | CHOI, JINKWANG | |
| O5 | Ginsenoside Rc prevents muscle atrophy by targeting TGF-β signaling and nucleolin expression under oxidative stress | Seokwon Kim | |
| O6 | Investigating potential drugs against the acquired resistance to EGFR Inhibitors based on Single-Cell Analysis | Heerim Yeo | |
| O7 | Predicting Drug-likeness through knowledge alignment and EM-like one-class boundary optimization | Dongmin Bang | |
| O8 | Multimodal molecular representation learning enhanced by chemical knowledge-based fragmentation for toxicity prediction | Sumin Ha | |
| O9 | Data Imputation for Connectivity Mapping Using Multivariate Normal Distribution Based Drug Correlation | Jiwon Jang | |
| P. Omics Data Integration & Analysis |
| P1 | CAPSMaker: A streamlined SNP-based high-throughput marker design system for realizing digital breeding in soybean | Joo-Seok Park | |
| P2 | Suppression of astrocytic immune responses by Nr3c1-mediated epigenetic regulation | Seongwan Park | |
| P3 | Development of a deep learning model for deconvolution of bulk in situ Hi-C by referencing pseudo-bulk single-cell epigenome profiles | Kyukwang Kim | |
| P4 | A Modification-Aware Framework for Fast Open Modification Spectral Library Search | Younghee Seo | |
| P5 | Systematic evaluation of dimensionality reduction methods for capturing diverse drug responses in drug-induced transcriptome | Yuseong Kwon | |
| P6 | A web-based system for comparative multi-omic analyses | WY SUYEON | |
| P7 | Integrative analysis of SARS-CoV-2 variants and clinical features for predicting disease progression using neural networks | Ha Soojung | |
| P8 | Differential Analysis of mRNA COVID-19 Vaccines in Muocarditis Patients through scRNA-seq and scATAC-seq Data | seul-gi Kim | |
| P9 | scDeepLUCIA: a deep-learning model to elucidate cell-type specific 3D gene regulation from low-resolution single-cell 3D genome information | Dongchan Yang | |
| P10 | Characterization of m6A modification patterns and their prognostic implications across various cancer types | Yebin Ryu | |
| P11 | Aberrant speckle-genome interaction facilitates oncogenic chromosomal translocations | Jaegeon Joo | |
| P12 | Inflammatory transcriptomic signatures and cell type compositions in inflamed and non-inflamed colonic mucosa of ulcerative colitis | JAHANZEB SAQIB | |
| P13 | NanoMnT: A STR analysis tool for Oxford Nanopore sequencing data driven by comprehensive analysis of error profile in STR regions | Gyumin Park | |
| P14 | Embedding Space Alignment of DNA and RNA Space for COVID-19 Severity Prediction Using Deep Learning | Inyoung Sung | |
| Q. ML and AI in Medicine and Healthcare |
| Q1 | Development of AI model for classifying immune phenotypes in lung cancer based on a novel approach utilizing whole transcriptomics | Ki Wook Lee | |
| Q2 | AIVariant1: a deep learning-based somatic variant detector for highly contaminated tumor samples | Junhak Ahn | |
| Q3 | DR.DEGMON: Self-explainable deep neural network for drug-induced cell viability prediction incorporating differentially expressed genes and Gene Ontology | wootaek Lim | |
| Q4 | Advancing MHC-Peptide Binding Prediction with Two-Dimensional Interaction Maps and Vision Transformer | Lee Jiho | |
| Q5 | ATOMIC : A graph attention neural network for ATOpy dermatitis prediction on human gut MICrobiome | Hyunsu Bong | |
| Q6 | Enhancing Molecular Property Prediction through Two-Stage Pre-training, Multi-Modal Fusion, and Scaffold Ensemble | Minyoung Kim | |
| Q7 | TransGOM: Transformer for Phenotype-based Molecular Generation using Gene Set Enrichment Scores | Jitae Kim | |
| Q8 | Codon optimization using Transformer and contrastive learning to enhance protein expression | Jeongmu Kim | |
| Q9 | Deep Transformer Model for Detecting driver signal in structural variation | Seo eun young | |
| Q10 | A bootstrap aggregating machine learning model for balanced prediction of androgen receptor agonistic toxicity with uncertainty quantification | Jidon Jang, Byung Ho Lee, Jeong Hyun Lee, Woo Dae Jang, Seung Hyeong Lee, Ho Won Seo, Mi Young Lee, Ye Sol Han, Su Ah Kim, Su Jin Park, Yumi Noh, Kwang-Seok Oh | |
| Q11 | Prediction of B cell immunodominance for vaccine design using statistical feature discovery and protein language model | Sungjin Choi | |
| Q12 | Leveraging machine learning on RNA-seq data for early discrimination of Alzheimer’s Disease from cognitively unimpaired individuals | Hyun Woo Park | |
| Q13 | Key biomarkers for predicting symptomatic SARS-CoV2 infection | Park Hyowon | |
| Q14 | ConFuseIT: Contrastive Learning-based Pretraining Model for Integrating Image and Transcriptomics for Multi-Task Prediction in Breast Cancer | Suwan Yu | |
| Q15 | pHLAHub: A Web-Based Consensus Prediction Tool for Peptide-HLA Binding and Epitope Analysis | Dongje Moon | |
| Q16 | Context-Aware Hierarchical Fusion for Drug Relational Learning | Yijingxiu Lu | |
| Q17 | Analysis of the influence of genetic and lifestyle factors on gout using machine learning | Do-Hyeon Kwak | |
| Q18 | Improving Protein Embeddings through Sequence-Structure Contrastive Learning | Min Su Yoon | |
| Q19 | Predicting Time-Concentration Profiles from Molecular Structures Using Artificial Intelligence Integrated with PBPK Modeling | Jeongyeon Lee | |
| Q20 | Optimization of Preprocessing Strategy for Developing a Machine Learning-based Disease Diagnosis Model Using Transcriptomics | Hye Jung Min | |
| R. Cancer Genomics |
| R1 | A Subset of Microsatellite Unstable Cancer Genomes Prone to Short Insertions over Deletions Is Associated with Elevated Anticancer Immunity | Sunmin Kim | |
| R2 | Evolutionary dependency of cancer mutations in gene pairs inferred by nonsynonymous-synonymous mutation ratios | Sunmin Kim | |
| R3 | Identification of single-cell and spatial markers associated with clinically relevant pathways in high-grade serous ovarian cancer | Dae Won Sim | |
| R4 | Identification of transcriptomic and epigenomic markers associated with FDG PET/CT in hepatocellular carcinoma | Ho-Jun Sung | |
| R5 | Genomic classification of intrapulmonary metastasis and multiple primary lung cancer | Jeongsoo Won | |
| R6 | Comparison analysis Between TSO500 Panel Sequencing and Whole Exome Sequencing in Patients with High-Grade Serous Carcinoma. | Ju-Won Kim | |
| R7 | CluVar: Clustering of variants using Autoencoder for inferring the phylogeny of cancer subclones in single cell RNA sequencing data | Chae won Kim | |
| R8 | Characterization of structural variants and germline mutations in early-onset breast cancer leveraging whole genome data | Se Jung Lee | |
| R9 | Characterization of the Genomic Alterations in Poorly Differentiated Thyroid Cancer | Yeeun Lee | |
| R10 | Discovering novel bispecific antibody targets for limited stage small cell lung cancer using machine learning at the single-cell RNA sequencing level | Gyo-Jin Choi | |
| S. Computational Drug Discovery (2)s |
| S1 | Cross-Attention Mechanisms for Drug Repositioning via Multi-modal Frameworks | Jae-woo Chu | |
| S2 | Transformer-Based Prediction of Drug Anatomical Therapeutic Chemical Code via Drug-Drug Interactions | Gwang-Hyeon Yun | |
| S3 | Scoring method of POM compound activity prediction for Mycobacterium tuberculosis | Jihyeon Yun | |
| S4 | De novo nanobody binder design using generative AI models | Hakyung Lee | |
| S5 | Development of a drug candidate discovery pipeline for Alzheimer's disease based on drug-transcriptomes | Kwon Minkyeong | |
| S6 | Predicting Morphological Profiles Associated with DNA Damage or Oxidative Stress Using Artificial Intelligence Models | Chaeyoung Seo | |
| S7 | Mixture-of-Experts Approach for Enhanced Drug-Target Interaction Prediction and Confidence Assessment | Yijingxiu Lu | |
| S8 | A Multimodal Approach for Predicting Drug Metabolism Using CYP2D6 Sequences and Drug Structures | Yeabean Na | |
| S9 | Development of Regression and Classification Models for Predicting CYP450 Enzyme Inhibition and Substrate Recognition | KO GEON | |
| S10 | Development of multi-task learning classification model for predicting CYP450 enzyme inhibition | Dong Ryeol Shin | |
| S11 | Machine Learning and Graph Neural Network-Based Prediction of Intestinal Permeability and Efflux Ratio: A Study on Caco-2 and MDCK Models | KOO NAYEONG | |
| S12 | In Silico Discovery of Novel Compounds for FAK Activation Using Virtual Screening, AI-Based Prediction, and Molecular Dynamics | Deokhyeon Yoon | |
| S13 | AI-Based Text Mining Platform for Information Collection and Analysis in Drug Discovery | JooHyun Kim | |
| T. Systems Biology |
| T1 | Reinforcement Learning-based Translational Fusion Partner Engineering | Seongbo Heo | |
| T2 | Predicting response to immune checkpoint blockade in patients with gynecological cancer | Kim donghyeon | |
| T3 | Comparative network-based analysis of toll-like receptor agonist, L-pampo™ signaling pathways in immune and cancer cells | Ahyoung Choi | |
| T4 | Identification of plausible target as an inter-organ target to mitigate cachexia while enhancing tumor suppression by anti-PD-L1 | Kyuwon Son | |
| T5 | Transcriptomic Analysis of Frequently Prescribed Herbal Medicines | Heeseon Jo | |
| T6 | Identifying Potential Therapeutic Targets for Heart Failure through Systematic Transcriptome Analysis | Min-Ju Kim | |
| U. Data Integration, Harmonization, and Ontology |
| U1 | RiceDBreeder: Integration and utilization of gwas and Korean rice phenotype, pedigree and resequencing data | DongU Woo | |
| U2 | Deep Learning-Based Prediction of Human Gene-Pathway Interactions using Gene and Pathway Literature information | Gyujin Son | |
| V. etc |
| V1 | In silico variant aware potential off-target site identification for genome editing applications | Mekonnen Abyot Melkamu | |
| V2 | Chromosome rearrangement and genome complexity in Hibiscus syriacus | Hyunjin Koo | |
| V3 | Efficient Cloud-Based Deployment of BioData Analysis Tools in K-BDS | Chan-Seok Jeong | |
| V4 | Comparative Evaluation of Deconvolution Methods for Bulk RNA-Sequencing in Blood Samples | Na Young Kwon | |
| V5 | Condition Aware Relational Learning for Chemical Reaction Yields Prediction | Yijingxiu Lu | |
| V6 | Causal variant effect prediction on cooked rice texture through integrative GWAS modelling | Dasol Kim | |
| V7 | Biofoundry based Automated Mutant Cloning Workflows | Jihyeon You | |