Computational Methods for Pathway and Network Analysis with MicroRNAs.

Inferring Gene Regulatory Networks in Stem Cells: Methods and Applications.

A multi-layer framework for computational cancer epigenomics

A structured multi-layer interpretation framework is proposed that links computational outputs across data-level processing, epigenomics-informed integrative regulatory modeling, and multi-omics-informed clinical interpretation, enabling traceable and mechanistically interpretable clinical inference.

Identification of Disease-miRNA Networks Across Different Human Complex Diseases Using SWIM and MIENTURNET Tools.

Integration of Omics Data to Identify Cancer-Related MicroRNA.

This chapter includes step-by-step protocols, example R code, and recommendations for integrating additional data layers such as copy number variation and DNA methylation, with the goal of improving the robustness and interpretability of miRNA-based analyses in cancer.

Integrative multi-omics and network biology in cardiovascular disease: a systems-level framework for translational discovery

This review provides a comprehensive, systems-level framework for translational discovery in cardiovascular disease, synthesizing advances in multi-omics technologies, network biology, artificial intelligence, and bioinformatics applied to conditions including thoracic aortic aneurysm, heart failure, valvular disease,...

A Framework for Analyzing the Epigenetic and Transcriptomic Landscape of Cancers Using Single-Cell Multiomic Data.

This chapter outlines a comprehensive protocol for joint embedding of chromatin accessibility and transcriptomic data using best practices developed in laboratories, along with detailed parameter tuning at each step to fully leveraging this pipeline.