Welcome
Multi-omics research is generating massive and complex data across genomics, transcriptomics, proteomics, metabolomics, epigenomics, microbiomics, and clinical phenotypes. These data offer great opportunities for understanding biological mechanisms, disease progression, drug response, and personalized medicine. However, high dimensionality, heterogeneity, noise, sparsity, and scale pose significant challenges for multi-omics data integration, storage, processing, interpretation, and analysis. Heuristic algorithms (HA) and pattern mining (PM) provide effective computational approaches for addressing these challenges.
HA can efficiently solve large-scale optimization problems in multi-omics analysis, while PM can discover hidden associations, biomarkers, regulatory motifs, disease-related patterns, and interpretable structures from biological datasets. Their combination with machine learning, deep learning, graph mining, and explainable AI can further enhance predictive modeling and biological interpretation.
Following the first edition of HP4MoDa at IEEE BIBM 2025, this second workshop aims to provide a forum to present recent advances, exchange ideas, and discuss open challenges in HA and PM for multi-omics data analytics. The aim is to explore cutting-edge techniques in this rapidly evolving field by providing a networking opportunity to bring together researchers and practitioners. By highlighting the intersection of data science and multi-omics, the HP4MoDa 2026 workshop will contribute to the broader goals of the IEEE BIBM 2026 conference, advancing knowledge in computational biology and data-driven multi-omics analytics.
Topics
The workshop will cover a wide range of topics, including but not limited to:
- Applications of HA and PM in genomics, transcriptomics, proteomics, and metabolomics.
- HA for multi-omics data integration and analysis.
- PM for identifying biomarkers, regulatory motifs, and functional elements.
- HA for optimizing sequence alignment and genome assembly in large-scale datasets.
- PM for associating genetic variants with diseases and phenotypic traits.
- HA for drug repurposing and virtual screening in drug discovery.
- PM for identifying therapeutic targets in cancer genomics and rare diseases.
- HA for optimizing clinical decision support systems using multi-omics data.
- Distributed and parallel HA for large-scale multi-omics data processing.
- Scalable PM algorithms for high-throughput sequencing data.
- Memory-efficient HA for handling high-dimensional omics datasets.
- Real-time PM techniques for dynamic and streaming omics data.
- Graph-based PM for analyzing biological networks (e.g., protein-protein interactions, gene regulatory networks).
- Swarm intelligence and evolutionary-based HA for multi-omics data analysis and pipeline optimization.
- Hybrid approaches combining HA and PM with ML for enhanced predictive modeling.
- Integration of HA and PM with deep learning for feature extraction and classification.
- Explainable AI (XAI) using HA for interpretable multi-omics analytics.
- HA and PM for single-cell multi-omics data analysis.
- PM for microbiome data analysis: Identifying microbial patterns linked to health or disease
- HA for long-read sequencing data analysis and error correction.
- HA for workflow optimization in multi-omics data pipelines
- Novel PM algorithms for high-dimensional and heterogeneous omics data.
- Quantum-inspired HA for multi-omics data optimization.
- Theoretical foundations of HA and PM in biological data analysis.
- Case studies of HA and PM in disease diagnosis, drug discovery, and personalized medicine.
- Real-world applications of PM in infectious disease surveillance and pathogen evolution.
- Open-source tools and frameworks for HA and PM in bioinformatics.
- Scalability and performance optimization in PM and ML algorithms
Publication
All accepted papers will be published in the IEEE Proceedings of the BIBM 2026 conference (indexed in EI and CCF-B).
A "best paper award" will be awarded for the best paper of the workshop.
Online participation
The HP4MoDa workshop will be held online. Thus, all authors can present their paper virtually.
Contact
For any questions, please contact the organizing committee.
