| Protein fitness prediction is impacted by the interplay of language models, ensemble learning, and sampling methods M Mardikoraem, D Woldring Pharmaceutics 15 (5), 1337, 2023 | 8 | 2023 |
| Generative models for protein sequence modeling: recent advances and future directions M Mardikoraem, Z Wang, N Pascual, D Woldring Briefings in Bioinformatics 24 (6), bbad358, 2023 | 7 | 2023 |
| Machine Learning-Driven Protein Library Design: A Path Toward Smarter Libraries M Mardikoraem, D Woldring Yeast Surface Display, 87-104, 2022 | 3 | 2022 |
| AP-LASR: Automated Protein Libraries from Ancestral Sequence Reconstruction J VanAntwerp, M Mardikoraem, N Pascual, D Woldring bioRxiv, 2023.10. 09.561537, 2023 | 1 | 2023 |
| EvoSeq-ML: Advancing Data-Centric Machine Learning with Evolutionary-Informed Protein Sequence Representation and Generation M Mardikoraem, DR Woldring ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 2024 | | 2024 |
| Affibody Sequence Design Using Deep Learning Generative Models Z Wang, M Mardikoraem, D Woldring PROTEIN SCIENCE 32, 2023 | | 2023 |
| Integration of protein engineering with machine learning to increase the efficiency of drug discovery J Eaves, M Mardikoraem, DR Woldring Biophysical Journal 121 (3), 46a, 2022 | | 2022 |
| Transfer Learning as a Superior Platform in Binding Affinity Prediction for Non-Immunoglobulin Scaffolds M Mardikoraem, D Woldring PROTEIN SCIENCE 30, 180-181, 2021 | | 2021 |
| Machine Learning Guides Combinatorial Protein Library Design M Mardikoraem, D Woldring 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
