C. K. Sruthi

This paper visualizes deep mutational scan data for TEM-1 β-lactamase to better understand mutation effects through attribute analysis.

The paper analyzes amino acid co-evolution in viral genomes to classify viral complexity using network characteristics and finds distinct patterns in different viruses.

The paper introduces a model that predicts phenotypic outcomes of protein mutations using sequence and structural data, improving prediction accuracy with random mutations over systematic substitutions.

The paper develops a microsimulation model to quantify how chemotaxis affects nutrient uptake and bacterial population growth, finding significant benefits only under nutrient-rich conditions.