Using Random Matrix Theory to Analyze Power Law Signatures in scRNA-seq Data

This 14-minute conference talk explores the application of Random Matrix Theory to analyze power law signatures in single-cell RNA sequencing (scRNA-seq) data, presented by Archishman Raju at the 10th Indian Statistical Physics Community Meeting. Learn how mathematical approaches from statistical physics can be applied to biological data analysis, specifically in understanding the complex patterns in gene expression at the single-cell level. The presentation is part of a broader discussion meeting organized by leading Indian physicists and hosted at the International Centre for Theoretical Sciences (ICTS-TIFR) in Bengaluru. The annual meeting brings together scientists, postdoctoral fellows, and graduate students from across India working in statistical physics, covering topics ranging from quantum systems and disordered materials to biological physics and complex systems.