Rooman, Marianne

BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations

Dehouck, Y., Kwasigroch, J. M., Rooman, M., & Gilis, D. (2013) · Nucleic Acids Research

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 338

Quantification of biases in predictions of protein stability changes upon mutations

Pucci, F., Bernaerts, K. V., Kwasigroch, J. M., & Rooman, M. (2018) · Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 169

SOLart: a structure-based method to predict protein solubility and aggregation

Hou, Q., Kwasigroch, J. M., Rooman, M., & Pucci, F. (2020) · Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 86

The Fefferman-Graham ambiguity and AdS black holes

Bautier, K., Englert, F., Rooman, M., & Spindel, P. (2000) · Physics Letters B

Black Holes and Theoretical PhysicsRelativity and Gravitational Theory

Cited by 33

Residue conservation and solvent accessibility are (almost) all you need for predicting mutational effects in proteins

Tsishyn, M., Hermans, P., Rooman, M., & Pucci, F. (2025) · Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 15

Residue conservation and solvent accessibility are (almost) all you need for predicting mutational effects in proteins

Tsishyn, M., Hermans, P., Pucci, F., & Rooman, M. (2025) · Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 15

Exploring Evolution to Uncover Insights Into Protein Mutational Stability

Hermans, P., Tsishyn, M., Schwersensky, M., Rooman, M., & Pucci, F. (2025) · Molecular Biology and Evolution

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 6