Integration of Transcriptomics and Proteomics in Systems Biology-Based Modeling of Gene Expression Regulation
Keywords:
Transcriptomics, Proteomics, Systems biology, Gene expression regulationAbstract
This study aims to analyze the integration of transcriptomics and proteomics in systems biology-based modeling of gene expression regulation. The issue examined in this study concerns the gap between RNA expression and protein abundance, which often creates challenges in interpreting biological mechanisms through a single omics layer. This research used a qualitative approach with an exploratory case study design. Data were collected through semi-structured interviews, limited observation, and scientific documentation involving researchers, lecturers, postgraduate students, bioinformatics analysts, and laboratory practitioners with experience in transcriptomic, proteomic, or multi-omics analysis. The data were analyzed using thematic analysis through data condensation, coding, theme development, and conclusion verification. The findings revealed five main themes: RNA-protein inconsistency, the interpretive role of computational tools, limitations in data quality and infrastructure, the need for interdisciplinary collaboration, and the construction of biological meaning from integrated data. These findings show that transcriptomics-proteomics integration is not merely a computational procedure, but also a scientific interpretation process shaped by biological reasoning, data context, and methodological decisions. This study contributes to the understanding of gene expression regulation as a multilayered and context-dependent phenomenon. The findings imply the need for stronger bioinformatics capacity, improved proteomic infrastructure, and further qualitative studies on multi-omics research practices in different scientific settings.
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