Seeing the trees through the forest: sequence-based homo-and heteromeric protein-protein interaction sites prediction using random forest Q Hou, PFG De Geest, WF Vranken, J Heringa, KA Feenstra Bioinformatics 33 (10), 1479-1487, 2017 | 57 | 2017 |
Computational analysis of the amino acid interactions that promote or decrease protein solubility Q Hou, R Bourgeas, F Pucci, M Rooman Scientific reports 8 (1), 1-13, 2018 | 50 | 2018 |
Parents’ decisions to vaccinate children against COVID-19: a scoping review F Pan, H Zhao, S Nicholas, E Maitland, R Liu, Q Hou Vaccines 9 (12), 1476, 2021 | 39 | 2021 |
A comprehensive computational study of amino acid interactions in membrane proteins MN Mbaye, Q Hou, S Basu, F Teheux, F Pucci, M Rooman Scientific reports 9 (1), 12043, 2019 | 38 | 2019 |
SOLart: a structure-based method to predict protein solubility and aggregation Q Hou, JM Kwasigroch, M Rooman, F Pucci Bioinformatics 36 (5), 1445-1452, 2020 | 37 | 2020 |
Club-martini: selecting favourable interactions amongst available candidates, a coarse-grained simulation approach to scoring docking decoys Q Hou, MF Lensink, J Heringa, KA Feenstra PloS one 11 (5), e0155251, 2016 | 19 | 2016 |
SeRenDIP: SEquential REmasteriNg to DerIve profiles for fast and accurate predictions of PPI interface positions Q Hou, PFG De Geest, CJ Griffioen, S Abeln, J Heringa, KA Feenstra Bioinformatics 35 (22), 4794-4796, 2019 | 16 | 2019 |
SeRenDIP-CE: sequence-based interface prediction for conformational epitopes Q Hou, B Stringer, K Waury, H Capel, R Haydarlou, F Xue, S Abeln, ... Bioinformatics 37 (20), 3421-3427, 2021 | 15 | 2021 |
Sequence specificity between interacting and non-interacting homologs identifies interface residues–a homodimer and monomer use case Q Hou, BE Dutilh, MA Huynen, J Heringa, KA Feenstra BMC bioinformatics 16 (1), 1-12, 2015 | 15 | 2015 |
SWOTein: a structure-based approach to predict stability strengths and weaknesses of prOTEINs Q Hou, F Pucci, F Ancien, JM Kwasigroch, R Bourgeas, M Rooman Bioinformatics 37 (14), 1963-1971, 2021 | 7 | 2021 |
Using metagenomic data to boost protein structure prediction and discovery Q Hou, F Pucci, F Pan, F Xue, M Rooman, Q Feng Computational and Structural Biotechnology Journal, 2022 | 3 | 2022 |
MPI-VGAE: protein–metabolite enzymatic reaction link learning by variational graph autoencoders C Wang, C Yuan, Y Wang, R Chen, Y Shi, T Zhang, F Xue, GJ Patti, L Wei, ... Briefings in Bioinformatics, bbad189, 2023 | | 2023 |
Enzyme stability-activity trade-off: new insights from protein stability weaknesses and evolutionary conservation Q Hou, M Rooman, F Pucci bioRxiv, 2023.05. 02.539073, 2023 | | 2023 |
Genome-scale enzymatic reaction prediction by variational graph autoencoders C Wang, C Yuan, Y Wang, R Chen, Y Shi, G Patti, Q Hou bioRxiv, 2023.03. 08.531729, 2023 | | 2023 |
From the hydrophobic core to the globular-disorder interface: New challenges and insights into protein design S Basu, D Chakravarty, Q Hou, VN Uversky Frontiers in Molecular Biosciences 10, 2023 | | 2023 |
Ten quick tips for sequence-based prediction of protein properties using machine learning Q Hou, K Waury, D Gogishvili, KA Feenstra PLOS Computational Biology 18 (12), e1010669, 2022 | | 2022 |
SWOTein: a structure-based approach to predict stability Strengths and Weaknesses of prOTEINs RB Kwasigroch, M Rooman | | 2021 |
Amino acid pair interactions in membrane proteins investigated with the statistical potential formalism MN Mbaye, Q Hou, F Pucci, M Rooman | | 2018 |
New statistical potentials for probing protein binding affinity at the interactome scale F Pucci, Q Hou, JM Kwasigroch, M Rooman FEBS JOURNAL 284, 43-44, 2017 | | 2017 |
Multi-Scale Investigation of Protein-Protein Interactions Q Hou | | 2017 |