Moretti, Rocco

Macromolecular modeling and design in Rosetta: recent methods and frameworks

Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 888

Engineering an allosteric transcription factor to respond to new ligands

Taylor, N. D., Garruss, A. S., Moretti, R., Chan, S., Arbing, M. A., Cascio, D., Rogers, J. K., Isaacs, F. J., Kosuri, S., Baker, D., et al. (2016) · Nature Methods

Gene Regulatory Network AnalysisMicrobial Metabolic Engineering and Bioproduction

Cited by 328

Self-supervised machine learning methods for protein design improve sampling but not the identification of high-fitness variants

Ertelt, M., Moretti, R., Meiler, J., & Schoeder, C. T. (2025) · Science Advances

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 15

Self-supervised machine learning methods for protein design improve sampling, but not the identification of high-fitness variants

Ertelt, M., Moretti, R., Meiler, J., & Schoeder, C. T. (2024) · Science Advances

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 15

Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors

Liu, Y., Moretti, R., Wang, Y., Dong, H., Yan, B., Bodenheimer, B., Derr, T., & Meiler, J. (2025) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 13