Future Direction: A PhD Connecting Discovery with Application
The unifying vision behind my interests is to make molecular knowledge more predictive, personalized, and widely accessible. I aspire to pursue a PhD that allows me to collaborate across diverse fields—bioinformatics, structural biology, oncology, and systems medicine—developing computational approaches rooted in biology and tailored for clinical translation. I am particularly eager to contribute to research groups working on:
- miRNA-driven regulatory pathways in cancer and immune systems
- Integrative multi-omics modeling for disease classification
- Machine learning frameworks for RNA-based therapeutics
Undertaking a PhD will not only provide the mentorship and infrastructure to achieve these aims but also position me to contribute meaningfully to a field where non-coding RNAs—once dismissed as “junk”—are now recognized as central to diagnostics and therapeutic innovation.
Conclusion
As global health is increasingly shaped by pandemics, precision medicine, and digital technologies, the intersection of RNA biology and artificial intelligence presents transformative opportunities. By advancing miRNA-focused diagnostics, multi-omics biomarker pipelines, and structure-informed predictive models, I aim to help redefine how complex diseases are detected and treated. My research goals are not just aspirations but a roadmap for diagnostic innovation, grounded in molecular biology and powered by computational methods.
To achieve this, I plan to embed structural and thermodynamic features into deep learning models—such as convolutional neural networks (CNNs) and transformer architectures—to capture layered relationships between RNA structure and function. I am especially interested in conserved RNA motifs at regulatory hotspots, including UTRs, pseudoknots, and stem-loop structures. By leveraging attention mechanisms, I hope to interpret which structural or energetic signals most strongly influence binding predictions.
One area of application is the study of structured viral RNAs, such as the HIV Rev Response Element (RRE), where host miRNAs may influence viral replication. More broadly, I intend to apply these approaches to cancer-associated transcripts, particularly within oncogenic and tumor suppressor pathways, where miRNA dysregulation is well documented but not yet fully understood at the systems level.