Publications

Bryn Marie Reimer, Vy Do, Anna G. Green (2026). Chemical space separation: Scaffold and UMAP splits are closer to random than we think. In ChemRxiv.

Mahbuba Tasmin, Shrishti Barethiya, Yu Wang, Lulu Kang, Jianhan G. Chen, Anna G. Green (2026). FARM: Forecasting Antibiotic Resistance in Mycobacterium tuberculosis using biophysics and machine learning. In bioRxiv.

Irene Lepori, Zichen Liu, Nelson Evbarunegbe, Shasha Feng, Turner P. Brown, Kishor Mane, Rachita Dash, Shivangi, Mitchell Wong, Ananya Naick, Amir George, Taijie Guo, Anil M. Shelke, K. Barry Sharpless, Jiajia Dong, Joel S. Freundlich, Wonpil Im, Anna G. Green, Marcos M. Pires, M. Sloan Siegrist (2026). Identification of chemical features for improved outer membrane permeation in mycobacteria using machine learning. In Nature Microbiology.

Nelson Evbarunegbe, Shiyun Wa, Luke Taylor, Anna G. Green (2026). ActiveFusion: Fused representations improve active learning for molecular property prediction. In ChemRxiv.

Bryn Marie Reimer, Anna G. Green (2026). A Frameshift Mutation in the Methyltransferase rlmN Is Associated with Increased Linezolid Resistance in Mycobacterium tuberculosis. In CSBJ.

Sanjana G. Kulkarni, Anna G. Green, Brendon C. Mann, Samantha Malatesta, Suchitra Kulkarni-Goodwin, Nina Cesare, Shandukani Mulaudzi, Noorjahn Rawoot, Robin M. Warren, Karen R. Jacobson, Maha R. Farhat (2026). Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response. In Nature Communications.

Nelson Evbarunegbe, Shiyun Wa, Isha Karn, Anna G. Green (2026). MycoPermeNet-v2: Improved Prediction of Mycomembrane Permeation Using Fusion Noisy Student Self-Distillation. In JCIM.

Mahbuba Tasmin, Saishradha Mohanty, Sanjana Kulkarni, Maha R. Farhat, Anna G. Green (2026). BIG-TB: A benchmark for prediction and interpretability of sequence-based machine learning using Mycobacterium tuberculosis genomes. In bioRxiv.

Anna G. Green, Mahbuba Tasmin, Roger Vargas Jr, Maha R. Farhat (2025). The structural context of mutations in proteins predicts their effect on antibiotic resistance. In bioRxiv.

Mariella Greutmann, Karsten Borgwardt, Sarah Brüningk, Fabian Franzeck, Christian G. Giske, Anna G. Green, Alejandro Guerrero-López, Margaret Ip, Catherine Jutzeler, Andre Kahles, Michael Krauthammer, Nenad Macesic, Benjamin McFadden, Eline Meijer, Nathan Moore, Jacob Moran-Gilad, Imane Lboukili, Oliver Nolte, Robin Patel, Gerold Schneider, Markus A. Seeger, Tavpritesh Sethi, Robert L. Skov, Chang Ho Yoon, Belén Rodríguez-Sánchez, Adrian Egli (2025). ESCMID workshop: Artificial intelligence and machine learning in medical microbiology diagnostics. In Microbes and Infection.

Jatin Nainani, Bryn Marie Reimer, Connor Watts, David Jensen, Anna G. Green (2025). Mechanistic evidence that motif-gated domain recognition drives contact prediction in protein language models. In bioRxiv.

Husain Poonawala, Yu Zhang, Sravya Kuchibotla, Anna G. Green, Daniela Maria Cirillo, Federico Di Marco, Andrea Spitlaeri, Paolo Miotto, Maha R. Farhat (2024). Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis. In JAAC.

Anna G. Green, Roger Vargas Jr, Maximillian G. Marin, Luca Freschi, Jiaqi Xie, Maha R. Farhat (2023). Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations. In MBE.

Anna G. Green, Chang Ho Yoon, Michael L. Chen, Yasha Ektefaie, Mack Fina, Luca Freschi, Matthias I. Groeschel, Isaac Kohane, Andrew Beam, Maha R. Farhat (2022). A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis. In Nature Communications.

Anna G. Green, Hadeer Elhabashy, Kelly P. Brock, Rohan Maddamsetti, Oliver Kohlbacher, Debora S. Marks (2021). Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences. In Nature Communications.

John M. Nicoludis, Anna G. Green, Sanket Walujkar, Elizabeth J. May, Marcos Sotomayor, Debora S. Marks, Rachelle Gaudet (2019). Interaction specificity of clustered protocadherins inferred from sequence covariation and structural analysis. In PNAS.

Thomas A. Hopf, Anna G. Green, Benjamin Schubert, Sophia Mersmann, Charlotta P. I. Schaerfe, John B. Ingraham, Agnes Toth-Petroczy, Kelly P. Brock, Adam J. Riesselman, Perry Palmedo, Chan Kang, Robert Sheridan, Eli J. Draizen, Christian Dallago, Chris Sander, Debora S. Marks (2018). The EVcouplings Python framework for coevolutionary sequence analysis. In Bioinformatics.