Aisha S.

Bioinformatics Specialization · Cohort 2024

Multi-Omics Data Analysis & Visualization to Investigate the Molecular Profile of Breast Cancer Cells in an Organ-on-a-Chip Model

The emergence of high-throughput multi-omics technologies facilitate the comprehensive analysis of different data, such as genomes, transcriptomes, proteomes, and metabolomes. Multi-omics data, however, require powerful analytical pipelines to generate meaningful biological insights. Here, we propose a novel integrated omics data(proteomics and transcriptomics) analysis pipeline that applies Gene Ontology (GO) enrichment, pathway enrichment, and Protein-Protein Interaction (PPI) network analyses to determine the mechanisms and pathways most involved in a breast cancer. Overall, this omics data analysis pipeline provides a robust methodology for interpreting large-scale biological data, facilitating the discovery of pathways, biomarkers, and drug targets in a disease environment. We apply this pipeline for breast cancer, but this methodology can be used for a variety of diseases.

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