导航分类PROGRAMME
August 21 | ||
3F, Tsinghua Southeast Asia Center | ||
Time | Program | Remark |
14:00 - 17:00 | Sign In | |
14:00 - 17:00 | Poster Preparation | |
16:00 - 17:00 | Social Hours | |
17:00 | Shuttle Bus Back to Prama Hotel / Sanur Area | |
August 22 | ||
Venue: Awan Auditorium, 3F | ||
Time | Program | Speaker |
08:20 - 09:00 | Sign In | |
09:00 - 09:05 | Opening | |
09:05 - 09:45 | Keynote Speech: AI co-scientists: the evolving role of Artificial Intelligence tools in science | Karin Verspoor(Executive Dean, School of Computing Technologies，RMIT University) |
09:45 - 10:10 | Invited Talk: Decoding 3D Gene Regulation with AI | In-Kyung Jeong (Steering Committee Member, Korea Society of Bioinformatics) |
10:10 - 10:35 | Invited Talk: Exosome Atlas DB: A Key Infrastructure for Biomarker Discovery | Sungho Ryu (President, Korea Society of Bioinformatics; Sooncheonhyang University) |
10:35 - 10:50 | Group Photo and Break | |
Session 1. Single‑Cell & Spatial Multi‑Omics Integration | ||
10:50 - 11:05 | Scalable sample demultiplexing in ultra-high-throughput scRNA-seq with HT-Demux | Xinzhu Jiang (Global College, Shanghai Jiao Tong University, Shanghai, China) |
11:05 - 11:20 | Decoding Hierarchical Cell-Cell Communication in Spatial Multi-Omics with CellSTIC | Yungang Xu (Xi'an Jiaotong University) |
11:20 - 11:35 | Grounded integration of single-cell multi-omics data with CITE-pool | Xinzhu Jiang (Global College, Shanghai Jiao Tong University, Shanghai, China) |
11:35 - 11:50 | TGDAC: Transformer-Based Graph Deep Clustering with Dual Distribution Alignment for single-cell RNA-seq | Zhendong Liu (Shanghai Polytechnic University) |
11:50 - 12:05 | Semantic-Aware Spatial Representation Learning for Spatial Domain Identification | Yawen Lu(hkust(gz)) |
12:05 - 13:15 | Lunch (Outside or in Tech Incubator Room, 3F) | |
13:15 - 13:30 | SPINNMF: Stable Spatial Transcriptional Program Discovery Linking Spatial Programs to Genetic Risk via Consensus Graph-Regularized Poisson NMF | Caicai Zhang (The University of Hong Kong) |
13:30 - 13:45 | Domain-Adversarial Multi-Scale Autoencoder for Cross-Sample and Cross-Platform Spatial Transcriptomics Integration | Dong Zhang (SJTU) |
13:45 - 14:00 | Safe Fusion for scRNA-seq Dropout Imputation with Uncertainty Gating and CITE-seq Validation | Lakshminarayanan Subramanian (New York University) |
14:00 - 14:15 | Intelligent ensemble learning for single cell data analysis | Hao Jiang (Renmin University of China) |
Session 2: Single-Cell Modeling & Perturbation Analysis | ||
14:15 - 14:30 | Stochastic Dynamics Inference and Applications Based on Landscape Theory | Chunhe Li (Fudan University) |
14:30 - 14:45 | VelODE Reconciles RNA Velocity and Developmental Trajectories for Robust Reconstruction of Cellular Dynamics | Yunhao Qiao (Shanghai Jiao Tong University) |
14:45 - 15:00 | iPerturb: Population-scale integration of multi-condition single-cell RNA-seq data to detect perturbation-responsive cell populations and genes | Ye Li (School of Public Health, Xi'an Jiaotong University) |
15:00 - 15:15 | CancerZigZag: Iterative Seed-Anchored Diffusion for Generative Modeling of Single-Cell State Transitions | Johannes Schlüter (Universität Bielefeld) |
15:15 - 15:30 | OmniCell: Unified Foundation Modeling of Single-Cell and Spatial Transcriptomics for Cellular and Molecular Insights | Jiangshuan Pang (BGI Research, Beijing) |
15:30 - 15:45 | Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining | Youzhe He (BGI research, Hang zhou) |
15:45 - 16:00 | How different AI models understand cells differently | Yubo Zhao (Tsinghua University) |
16:00 - 16:15 | A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions | Xi Xi (Beijing Institute of Technology) |
16:15 - 16:30 | Break | |
16:30 - 17:45 | Panel Discussion | |
18:00 - 19:30 | Welcome Dinner | |
20:00 | Shuttle Bus Back to Prama Hotel / Sanur Area | |
August 23 | ||
Venue: Awan Auditorium, 3F | ||
Time | Program | Speaker |
08:20 - 09:00 | Registration | |
09:00 - 09:05 | Opening | |
09:05 - 09:45 | Keynote Speech: Seq2image: A Holistic Image-Based Paradigm for Genomic Sequence Analysis | Kai Ye (Xi’an Jiaotong University) |
09:45 - 10:10 | Invited Talk: Data and AI-driven Exploration of the Human Gut Microbiome | Xing-Ming Zhao (Fudan University) |
10:10 - 10:35 | Invited Talk: Spatiotemporal Proteomics for Constructing Virtual Cell Models | Tian-Nan Guo (Westlake University) |
10:35 - 10:50 | Break | |
Session 3: Sequence Modeling: from DNA to RNA | ||
10:50 - 11:05 | Profiling genomic language models as individuals in a population | Yusen Hou (The Hong Kong University of Science and Technology (Guangzhou)) |
11:05 - 11:20 | Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications | Ningyuan You (Zhejiang University) |
11:20 - 11:35 | R-loop Prediction Reveals Generalization Limits of DNA Foundation Models Beyond Regulatory Genomics | Yafan Zhang (Bioinformatics Research Center, North Carolina State University) |
11:35 - 11:50 | LUNA-FM: A subword foundation model for long non-coding RNAs for functional inference | Naima Vahab (RMIT University) |
11:50 - 12:05 | Toward a paradigm shift from data to theory: AI-driven representation of biological sequences | Zhang Zhang (China National Center for Bioinformation) |
12:05 - 13:15 | Lunch (Outside or in Tech Incubator Room, 3F) | |
13:15 - 13:30 | CyanoDiff: Class-Conditional Cyanobacterial Promoter Generation via Masked Diffusion Language Modeling | Guang Yang (School of Life Science and Technology, Northwestern Polytechnical University) |
13:30 - 13:45 | Context-aware prediction of RNA-centric interactions using deep learning | Bin Zhang (Mohamed Bin Zayed University of Artificial Intelligence) |
13:45 - 14:00 | PHOCI: Predictor of Higher-Order Chromatin Interactions | Kai Huang (Shenzhen Bay Laboratory) |
14:15 - 14:30 | Retracing the Process of Translation: Proteome-wide mapping of stable transcriptomic predictors of protein abundance in cancer cell lines | Johannes Schlüter (Universität Bielefeld) |
14:30-14:45 | Break | |
Session 4: Protein Structure, Interaction & Molecular Design | ||
14:45 - 15:00 | AlphaFold 3 Fails to Predict D-peptide Chirality, Fold, and Binding Pose in Heterochiral Complexes | Henry Childs (Duke University) |
15:00 - 15:15 | An Improved Significance Metric for Searching Protein Motifs with Folddisco | Jaewon Yoon (Seoul National University) |
15:15 - 15:30 | MolX: A Geometric Foundation Model for Protein-Ligand Modelling | Fuyi Li (Adelaide University) |
15:30 - 15:45 | InteractionFormeR: SE(3)-Equivariant Proteome-Scale Interactome Simulation on Resource-Constrained Hardware | Aaryan Senthilvanan (S.Y.A.L.I.S Labs) |
15:45 - 16:00 | CCK* (Convex Closure K*): A Suite of Algorithms for De Novo L- and D-peptide Design | Henry Childs (Duke University) |
16:00 - 16:15 | Tri-Modality Representation Learning for Molecular Property Prediction | Jing Li (Case Western Reserve University) |
16:15 - 17:30 Poster Flash Talk | ||
17:30 | Shuttle Bus Back to Prama Hotel / Sanur Area | |
August 24 | ||
Venue: Awan Auditorium, 3F | ||
Time | Program | Speaker |
09:00 - 09:05 | Opening | |
Session 5: Multi‑Omics Integration, Disease Prediction & Biomedical Reasoning | ||
09:05 - 09:20 | Strategies for Constructing Central Dogma Foundation Model (CDFM) for Medical Needs | Sun Kim (Seoul National University / AIGENDRUG Co. Ltd) |
09:20 - 09:35 | BioREASONIC: A Causal-Oriented GraphRAG System for Multi-Omics Biomedical Reasoning | Sakhaa Alsaedi (King Abdullah University of Science and Technology (KAUST)) |
09:35 - 09:50 | MoPE-MOI: A Mixture-of-Pathway-Experts Framework for Interpretable Multi-Omics Integration | Zhe Liu (Seoul National University) |
09:50 - 10:05 | GAE-Delta: A Graph-Learning Framework for Gene Network Rewiring and Clinical Outcome Prediction from Multi-Omics Data | Zhiyong Tang (University of Southampton) |
10:05 - 10:20 | Profiling Gastrointestinal Cancer Subtypes through Integrated Analysis of Tumor Microenvironment Genomic and Microbial Features | Xiaoyang Wang (University of Science and Technololy Beijing) |
10:20 - 10:35 | Learning Shift-Invariant Graph Representations for Cox Survival on Multi-Modal Cancer Data | Lingxi Chen (City University of Hong Kong) |
10:35 - 10:50 Break | ||
10:50 - 11:05 | A Deep Representation Learning Method for Quantitative Immune Defense Function Evaluation and Its Clinical Applications | An-Yuan Guo (Sichuan University) |
11:05 - 11:20 | Patient-level drug response prediction through dual adversarial alignment of pre- and post-drug treatment transcriptomic states | Sugyun An (AIGENDRUG) |
11:20 - 11:35 | ROCKET: Risk-Oriented Causal Knowledge - Enriched Topology for Enhancing Healthcare Predictions | Sakhaa Alsaedi (King Abdullah University of Science and Technology (KAUST)) |
11:35 - 11:50 | DeepMAP: A Pretrained Multimodal Framework for Connecting Disease with Therapeutic Compounds | Zhi Huang (The Hong Kong University of Science and Technology) |
11:50 - 12:05 | synerOmics: Machine Learning-Driven Discovery of Synergistic Protein Interactions Underlying Cancer Drug Response | Priya Ramarao-Milne (CSIRO) |
12:05 - 13:15 | Lunch (Outside or in Tech Incubator Room, 3F) | |
13:15 - 13:30 | CancerGen-RAG: A Framework for Scalable Lung Cancer Variant Prioritization and Interpretation | |
13:30 - 13:45 | Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis | Zexian Liu (Sun Yat-sen University Cancer Center) |
13:45 - 14:00 | SPRINT: A SNP-PRS Residual Integration Model for Complex Disease Genetic Risk Prediction | |
14:00 - 14:15 | WACA-DTA: Logit-Level Geometric and Hydration Biases for Structure-Conditioned Drug - Target Affinity Prediction | Kehan Huang (China pharmauciutical university) |
Session 6: Fitness and Cross-Species | ||
14:15 - 14:30 | ArchaicSeeker 3.0: A deep-learning framework for scalable, haplotype-resolved inference of archaic introgression | Shuhua Xu (Fudan University) |
14:30 - 14:45 | CrossGapFilling: Context-Aware Deep Learning for Cross-Species Metabolic Network Gap-Filling | Ziwei Yang (Chugai Pharmaceutical Co., Ltd.) |
14:45 - 15:00 | ANIMA: A Cross-Species Approach for Protein-Protein Interaction Prediction | Bruno Rafael Florentino (University of São Paulo) |
15:15 - 15:30 Closing | ||
15:30 - 16:30 Poster & Exhibitions | ||
16:30 Shuttle Bus Back to Prama Hotel/Sanur Area | ||
