Decoding the Genetic Networks of Addiction: High-Performance Computing for Insight into Opioid and Nicotine Dependency
Date:
Short Talk at Platform for Advanced Scientific Computing (PASC) 2024 Conference, Zurich, Switzerland
This talk presented novel advances in the integration of large-scale biological data using multiplex network models with Random Walk with Restart (RWR) approaches to embed and cluster genes for downstream analysis.
Topics covered:
- Integration of genomics, transcriptomics, proteomics, and metabolomics into multiplex networks using mixed integration strategies for downstream multiomic analysis.
- Generation of cell-type-specific predictive expression networks (scPENs) from single-cell RNA-seq data, using iRF-loop and RWRtoolkit.
- Construction of a 25-layer human prefrontal cortex multiplex network to understand opioid use disorder and smoking cessation overlap.
- Application of the MENTOR framework (Multiplex Embedding of Networks for Team-Based Omics Research) for gene clustering.