(last updated October 30, 2021; also see Google Scholar)


Tu, Z., Coley, C. W. Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction. arxiv:arXiv:2110.09681 (2021)

Gao, W., Mercado, R., Coley, C. W. Amortized tree generation for bottom-up synthesis planning and synthesizable molecular design. arxiv:2110.06389 (2021)

Adams, K., Pattanaik, L., Coley, C. W. Learning 3D representations of molecular chirality with invariance to bond rotations. arxiv:2110.04383 (2021)

Coley, C. W., Wang, X. Understanding, predicting, and optimizing biomolecular interactions with machine learning. Curr. Opin. Chem. Biol. DOI: 10.1016/j.cbpa.2021.08.009 (2021)

Fu, T., Gao, W., Xiao, C., Yasonik, J., Coley, C. W., Sun, J. Differentiable scaffolding tree for molecular optimization. arxiv:2109.10469 (2021)

Goldman, S., Das, R., Yang, K. K., Coley, C. W. Machine learning modeling of family wide enzyme-substrate specificity screens. 2109.03900 (2021)

Lim, K. S., Reidenbach, A. G., Hua, B. K., Mason, J. W., Gerry, C. J., Clemons, P. A., Coley, C. W. Machine learning on DNA-encoded library count data using an uncertainty-aware probabilistic loss function. arxiv:2108.12471 (2021)

Stuyver, T., Coley, C. W. Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability and interpretability. arxiv:2107.10402 (2021)

Soleimany, A. P., Amini, A., Goldman, S., Rus, D., Bhatia, S., Coley, C. W. Evidential deep learning for guided molecular property prediction and discovery. ACS Cent. Sci. DOI:10.1021/acscentsci.1c00546 (2021) and NeurIPS ML4Molecules. (2020) [spotlight talk]

Bi, H.*, Wang, H.*, Shi, C., Coley, C. W., Tang, J., Guo, H. Non-autoregressive electron redistribution modeling for reaction prediction. arxiv:2106.07801 (2021)

Ganea, O. E.*, Pattanaik, L.*, Coley, C. W., Barzilay, R., Jensen, K. F., Green, W. H., Jaakkola, T. S. GeoMol: Torsional geometric generation of molecular 3D conformer ensembles. arxiv:2106.07802 (2021)

Guo, J., Ibanez-Lopez, A. S., Gao, H., Quach, V., Coley, C. W., Jensen, K. F., Barzilay, R. Automated chemical reaction extraction from scientific literature. J. Chem. Inf. Model. (2021)

Zheng, S., Zeng, T., Li, C., Chen, B., Coley, C. W., Yang, Y., Wu, R. BioNavi-NP: Biosynthesis navigator for natural products. arxiv:2105.13121 (2021)

Heid, E., Goldman, S., Sankaranarayanan, K., Coley, C. W., Flamm, C., Green, W. H. EHreact: Extended Hasse diagrams for the extraction and scoring of enzymatic reaction templates. Chemrxiv DOI: 10.26434/chemrxiv.14714748.v1 (2021).

Huang, K., Fu, T., Gao, W., Zhao, Y., Roohani, Y., Leskovec, J., Coley, C. W., Xiao, C., Sun, J., Zitnik, M. Therapeutics Data Commons: Machine learning datasets and tasks for therapeutics. arXiv:2102.09548 (2021).

Graff, D. E., Shakhnovich, E. I., Coley, C. W. Accelerating high-throughput virtual screening through molecular pool-based active learning. Chem. Sci. 12, 7866-7881 (2021).

Guan, Y., Coley, C. W., Wu, H., Ranasinghe, D., Heid, E., Struble, T. J., Pattanaik, L., Green, W. H., Jensen, K. F. Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors. Chem. Sci. 12, 2198-2208 (2021)


Coley, C. W. Defining and exploring chemical spaces. Trends in Chemistry DOI: 10.1016/j.trechm.2020.11.004 (2020).

Gao, H., Pauphilet, J., Struble, T. J., Coley, C. W., Jensen, K. F. Direct optimization across computer-generated reaction networks balances materials use and feasibility of synthesis plans for molecule libraries. J. Chem. Inf. Model. DOI: 10.1021/acs.jcim.0c01032 (2020).

Mo, Y., Guan, Y., Verma, P., Guo, J., Fortunato, M. E., Lu, Z., Coley, C. W., Jensen, K. F. Evaluating and clustering retrosynthesis pathways with learned strategy. Chem. Sci. DOI: 10.1039/D0SC05078D (2020).

Pattanaik, L., Ganea, O. E., Coley, I., Jensen, K. F., Green, W. H., Coley, C. W. Message passing networks for molecules with tetrahedral chirality. NeurIPS ML4Molecules, arxiv:2012.00094. (2020) [spotlight talk]

Wang, X., Qian, Y., Gao, H., Coley, C. W., Mo, Y., Barzilay, R., Jensen, K. F. Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning. Chem. Sci. 11, 10959-10972 (2020)

V. R. Somnath, C. Bunne, C. W. Coley, A. Krause, R. Barzilay. Learning graph models for template-free retrosynthesis. (2020), arxiv:2006.07038

L. Pattanaik, C. W. Coley, Molecular representation: Going long on fingerprints. Chem. 6, 1204-1207 (2020)

L. Hirschfeld, K. Swanson, K. Yang, R. Barzilay, C. W. Coley, Uncertainty quantification using neural networks for molecular property prediction. (2020), arxiv:2005.10036

Struble, T. S., Alvarez, J. C., Brown, S., Chytil, M., Cisar, J., DesJarlais, R., Engkvist, O., Frank, S. A., Greve, D. R., Griffin, D. J. Hou, X., Johannes, J. W., Kreatsoulas, C., Lahue, B., Mathea, M., Mogk, G., Nicolaou, C. A., Palmer, A. D., Price, D. J., Robinson, R. I., Salentin, S., Xing, L., Jaakkola, T., Green, W. H., Barzilay, R., Coley, C. W., Jensen, K. F., Current and future roles of artificial intelligence in medicinal chemistry synthesis. J. Med. Chem. (2020), DOI:10.1021/acs.jmedchem.9b02120

W. Gao, C. W. Coley, The synthesizability of molecules proposed by generative models. (2020), arxiv:2002.07007

T. J. Struble, C. W. Coley, K. F. Jensen, Multitask Prediction of Site Selectivity in Aromatic C-H Functionalization Reactions. React. Chem. Eng. (2020) (preprint).

Fortunato, M. E., C. W. Coley, Barnes, B. C., Jensen, K. F. Data augmentation and pretraining for template-based retrosynthetic prediction in computer-aided synthesis planning. (2020), 10.26434/chemrxiv.11811564.v1

H. Gao, C. W. Coley, T. Struble, L. Li, Y. Qian, W. H. Green, K. F. Jensen, Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list. React. Chem. Eng. (2020), doi:10.1039/C9RE00348G


H. Dai, C. Li, C. W. Coley, B. Dai, L. Song, Retrosynthesis prediction with conditional graph logic network. NeurIPS (2019)

C. W. Coley, N. S. Eyke, K. F. Jensen, Autonomous Discovery in the Chemical Sciences Part II: Outlook. Angew. Chem. Int. Ed. (2019), doi:10.1002/anie.201909989 (preprint)

C. W. Coley, N. S. Eyke, K. F. Jensen, Autonomous Discovery in the Chemical Sciences Part I: Progress. Angew. Chem. Int. Ed. (2019), doi:10.1002/anie.201909987 (preprint)

T.-S. Lin, C. W. Coley, H. Mochigase, H. K. Beech, W. Wang, Z. Wang, E. Woods, S. L. Craig, J. A. Johnson, J. A. Kalow, K. F. Jensen, B. D. Olsen, BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules. ACS Cent. Sci. (2019), doi:10.1021/acscentsci.9b00476.

C. W. Coley, D. A. Thomas, J. A. M. Lummiss, J. N. Jaworski, C. P. Breen, V. Schultz, T. Hart, J. S. Fishman, L. Rogers, H. Gao, R. W. Hicklin, P. P. Plehiers, J. Byington, J. S. Piotti, W. H. Green, A. J. Hart, T. F. Jamison, K. F. Jensen, A robotic platform for flow synthesis of organic compounds informed by AI planning. Science. 365, eaax1566 (2019).

K. Yang, K. Swanson, W. Jin, C. Coley, P. Eiden, H. Gao, A. Guzman-Perez, T. Hopper, B. Kelley, M. Mathea, A. Palmer, V. Settels, T. Jaakkola, K. Jensen, R. Barzilay, Analyzing Learned Molecular Representations for Property Prediction. J. Chem. Inf. Model. 59, 3370–3388 (2019).

C. W. Coley, W. H. Green, K. F. Jensen, RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application. J. Chem. Inf. Model. 59, 2529–2537 (2019).

J. S. Schreck, C. W. Coley, K. J. M. Bishop, Learning Retrosynthetic Planning through Simulated Experience. ACS Cent. Sci. 5, 970–981 (2019).

C. W. Coley, W. Jin, L. Rogers, T. F. Jamison, T. S. Jaakkola, W. H. Green, R. Barzilay, K. F. Jensen, A graph-convolutional neural network model for the prediction of chemical reactivity. Chem. Sci.. 10, 370–377 (2019).


H. Gao, T. J. Struble, C. W. Coley, Y. Wang, W. H. Green, K. F. Jensen, Using Machine Learning To Predict Suitable Conditions for Organic Reactions. ACS Cent. Sci. 4, 1465–1476 (2018).

C. Zhu, K. Raghuvanshi, C. W. Coley, D. Mason, J. Rodgers, M. E. Janka, M. Abolhasani, Flow chemistry-enabled studies of rhodium-catalyzed hydroformylation reactions. Chemical Communications. 54, 8567–8570 (2018).

C. W. Coley, W. H. Green, K. F. Jensen, Machine Learning in Computer-Aided Synthesis Planning. Acc. Chem. Res. 51, 1281–1289 (2018).

L. M. Baumgartner, C. W. Coley, B. J. Reizman, K. W. Gao, K. F. Jensen, Optimum catalyst selection over continuous and discrete process variables with a single droplet microfluidic reaction platform. React. Chem. Eng.. 3, 301–311 (2018).

H.-W. Hsieh, C. W. Coley, L. M. Baumgartner, K. F. Jensen, R. I. Robinson, Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor. Org. Process Res. Dev. 22, 542–550 (2018).

R. W. Epps, K. C. Felton, C. W. Coley, M. Abolhasani, A Modular Microfluidic Technology for Systematic Studies of Colloidal Semiconductor Nanocrystals. J Vis Exp (2018), doi:10.3791/57666.

S. Lazzari, P. M. Theiler, Y. Shen, C. W. Coley, A. Stemmer, K. F. Jensen, Ligand-Mediated Nanocrystal Growth. Langmuir. 34, 3307–3315 (2018).

C. W. Coley, L. Rogers, W. H. Green, K. F. Jensen, SCScore: Synthetic Complexity Learned from a Reaction Corpus. J. Chem. Inf. Model. 58, 252–261 (2018).

Y. Shen, M. Abolhasani, Y. Chen, L. Xie, L. Yang, C. W. Coley, M. G. Bawendi, K. F. Jensen, In-Situ Microfluidic Study of Biphasic Nanocrystal Ligand-Exchange Reactions Using an Oscillatory Flow Reactor. Angewandte Chemie International Edition, 16333–16337 (2018).


C. W. Coley, L. Rogers, W. H. Green, K. F. Jensen, Computer-Assisted Retrosynthesis Based on Molecular Similarity. ACS Cent. Sci. 3, 1237–1245 (2017).

R. W. Epps, K. C. Felton, C. W. Coley, M. Abolhasani, Automated microfluidic platform for systematic studies of colloidal perovskite nanocrystals: towards continuous nano-manufacturing. Lab on a Chip. 17, 4040–4047 (2017).

W. Jin, C. Coley, R. Barzilay, T. Jaakkola, in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett, Eds. (Curran Associates, Inc., 2017;, pp. 2607–2616.

C. W. Coley, R. Barzilay, W. H. Green, T. S. Jaakkola, K. F. Jensen, Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction. J. Chem. Inf. Model. 57, 1757–1772 (2017).

C. W. Coley, M. Abolhasani, H. Lin, K. F. Jensen, Material-Efficient Microfluidic Platform for Exploratory Studies of Visible-Light Photoredox Catalysis. Angewandte Chemie. 129, 9979–9982 (2017).

C. W. Coley, R. Barzilay, T. S. Jaakkola, W. H. Green, K. F. Jensen, Prediction of Organic Reaction Outcomes Using Machine Learning. ACS Cent. Sci. 3, 434–443 (2017).

Y.-J. Hwang, C. W. Coley, M. Abolhasani, A. L. Marzinzik, G. Koch, C. Spanka, H. Lehmann, K. F. Jensen, A segmented flow platform for on-demand medicinal chemistry and compound synthesis in oscillating droplets. Chemical Communications. 53, 6649–6652 (2017).


M. Abolhasani, C. W. Coley, K. F. Jensen, Multiphase Oscillatory Flow Strategy for in Situ Measurement and Screening of Partition Coefficients. Anal. Chem. 87, 11130–11136 (2015).

M. Abolhasani, C. W. Coley, L. Xie, O. Chen, M. G. Bawendi, K. F. Jensen, Oscillatory Microprocessor for Growth and in Situ Characterization of Semiconductor Nanocrystals. Chem. Mater. 27, 6131–6138 (2015).