• Deep dive into machine learning models for protein engineering. Verma D, PEGS Boston 2022

• Invention of an ideal synthesis of molnupiravir, a COVID-19 antiviral. Verma D, ACS Spring, 2022

• Deep dive into machine learning models for directed-evolution of enzymes. Verma D, Applied Biocatalysis Summit, 2021

• Enzymatic cascades: Producing small molecules using green chemistry. Verma D, Murphy G, RosettaCON Leavenworth, 2019

• Designing small HIV-1 antigens by protein peeling and rewiring techniques. Verma D, Lai J, Brown E, Ackerman M, Bailey-Kellogg C, ISMB 3DSIG Orlando, 2016.

• Structure-based design of combinatorial mutagenesis libraries. Verma D, Grigoryan G and Bailey-Kellogg C, ISMB Boston, 2014.

• Is rigidity conserved across the class A β-lactamase family? Verma D and Livesay DR, Biophysical Journal, Volume 102, Issue 3, 2012, 458a.

• Elucidating the effects of mutation upon c-type lysozyme through quantitative stability/flexibility relationships. Verma D, Jacobs DJ and Livesay DR, Biophysical Journal, Volume 100, Issue 3, 2011, 400a.

• Towards comprehensive analysis of protein family quantitative stability/flexibility relationships. Verma D, Jacobs DJ, Guo J and Livesay DR, Biophysical Journal, Volume 98, Issue 3, 2010, 637a.

• Predicting protein mutant stability with a combined experimental/theoretical approach. Verma D, Jacobs DJ and Livesay DR, Biophysical Journal, Volume 96, Issue 3, 2009, 301a.

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