Momina Dilshad
Papers
1
Total Citations
16
H-Index
1
About
Momina Dilshad is a rising interdisciplinary researcher at the forefront of nanobiotechnology and computational oncology. Her work uniquely bridges green nanomaterial synthesis with deep learning, targeting the molecular underpinnings of cancer. Her most cited study, "Incubating Green Synthesized Iron Oxide Nanorods for Proteomics-Derived Motif Exploration: A Fusion to Deep Learning Oncogenesis" (2022, 16 citations), exemplifies this fusion. Here, she pioneered the eco-friendly fabrication of crystalline iron oxide nanorods (average 17.32 nm), rigorously characterized via UV-visible spectroscopy, XRD, FTIR, and nano-LC mass spectrometry. The true innovation lies in deploying these nanorods as a proteomics tool to isolate and explore peptide motifs, which she then integrated with a deep learning model to predict oncogenic patterns. This work not only demonstrates a sustainable pathway for nanomaterial synthesis but also creates a powerful analytical pipeline for early cancer biomarker discovery. By merging experimental nanotechnology with computational biology, Dilshad is carving a novel niche that promises to accelerate the identification of cancer-driving molecular signatures, offering a compelling blueprint for future precision oncology research.
Research Focus
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Top Papers
- 1