(Include but not limited to)
Track 1: Bioinformatics
Advanced algorithms for biological sequence and structure analysis
New methods for AI-driven protein structure prediction and molecular docking
Systems biology and multi-scale biological network modeling
Computational immunoinformatics and vaccine design
Chemical informatics and structure-based drug discovery
Biomedical signal processing and medical informatics
Interpretable artificial intelligence (XAI) in bioinformatics
Bio-molecular design based on generative models and synthetic biology simulation
Biomedical text mining and knowledge discovery (such as literature retrieval, relationship extraction)
Biomedical image analysis and computational pathology
High-performance computing and workflow management in bioinformatics
Population genetics and evolutionary bioinformatics
Computational methods for single-cell and spatial transcriptomics data
Biomolecular dynamics simulation and force field development
Track 2: Genomics
Analysis of genomes, transcriptomes, proteomes and metabolomes
Single-cell sequencing data analysis and spatial omics techniques
Comparative genomics, population genetics and evolutionary biology
Metagenomics and microbial group data analysis
Cancer genomics and computational oncology
Structural bioinformatics and protein structure prediction
Gene regulatory networks and systems biology modeling
Drug target discovery and computational drug design
Epigenetics and functional genomics
Phylogenetics and molecular evolution analysis
Reconstruction of biological networks and pathway analysis
Development of bioinformatics algorithms, models and software tools
Integration and modeling of multi-omics data
Deployment of bioinformatics Pipelines in cloud and edge computing architectures
Automatic construction of knowledge graphs from biomedical text mining
Association analysis of electronic health records (EHR) and genomic data
Interactive visualization and exploratory analysis tools for bioinformatics data
Application of scientific workflow management systems in bioinformatics data
Biological data lake architecture and distributed storage solutions
Analysis of biological molecule interaction networks based on graph neural networks
Spatio-temporal omics and developmental biology data modeling
Quality assessment of bioinformatics data and batch effect correction methods
Application of generative AI in data augmentation of biological sequences and structures
......