Understanding genetic interactions is crucial for unraveling the complex architecture of diseases and traits, yet their detection poses significant statistical and computational challenges.
This article provides a comprehensive guide to regression-based models for epistasis analysis, tailored for researchers and drug development professionals.
Complex diseases like cancer, Alzheimer's, and cardiovascular disorders demand precision medicine approaches that move beyond broad classifications.
This article provides a comprehensive overview of dynamic modeling approaches for predicting and understanding drug responses within the framework of systems biology.
This article provides a comprehensive overview of static network modeling for elucidating disease mechanisms, tailored for researchers, scientists, and drug development professionals.
The complexity of cancer and other complex diseases demands a paradigm shift beyond single-molecule biomarkers.
This article provides a comprehensive overview of module identification in biological networks and its pivotal role in understanding complex diseases.
Pathway enrichment analysis has become an indispensable knowledge-based approach for interpreting high-throughput omics data in complex disease research.
This article provides a comprehensive overview of the pivotal role Protein-Protein Interaction (PPI) networks play in understanding complex diseases and advancing therapeutic development.
This article provides a comprehensive overview of the rapidly evolving field of Gene Regulatory Network (GRN) inference, a critical computational challenge in systems biology and drug discovery.