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| 2020 | von Lilienfeld | Retrospective on a decade of machine learning for chemical discovery | Nature Communications |
| 2020 | Lopez | Enhancing scientific discoveries in molecular biology with deep generative models | Molecular Systems Biology |
| 2020 | Cao | Ensemble deep learning in bioinformatics | Nature Machine Intelligence |
| 2020 | Kopp | Deep learning for genomics using Janggu | Nature Communications |
| 2020 | Adam | Machine learning approaches to drug response prediction: challenges and recent progress | npj Precision Oncology |
| 2020 | Schreiber | Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome | Genome biology |
| 2020 | Schreiber | Completing the ENCODE3 compendium yields accurate imputations across a variety of assays and human biosamples | Genome biology |
| 2020 | Brown | Artificial intelligence in chemistry and drug design | Journal of Computer-Aided Molecular Design |
| 2020 | van der Schaar | How artificial intelligence and machine learning can help healthcare systems respond to COVID-19 | Group website |
| 2020 | Neves | Deep Learning-driven research for drug discovery: Tackling Malaria | PLOS Computational Biology |
| 2020 | Stokes | A Deep Learning Approach to Antibiotic Discovery | Cell |
| 2020 | Xu | A comprehensive review of computational prediction of genome-wide features | Briefings in Bioinformatics |
| 2020 | Walters | Assessing the impact of generative AI on medicinal chemistry | Nature Biotechnology |
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| 2019 | Schneider | Rethinking drug design in the artificial intelligence era | Nature Reviews Drug Discovery |
| 2019 | Dias | Artificial intelligence in clinical and genomic diagnostics | Genome Medicine |
| 2019 | Filipp | Opportunities for artificial intelligence in advancing precision medicine | arXiv |
| 2019 | Yang | Machine-learning-guided directed evolution for protein engineering | Nature methods |
| 2019 | Kopp | Janggu - Deep learning for genomics | bioRxiv |
| 2019 | Zhavoronkov | Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity | Trends in Pharmacological Sciences |
| 2019 | Mater | Deep Learning in Chemistry | J. Chem. Inf. Model. |
| 2019 | Eraslan | Deep learning: new computational modelling techniques for genomics | Nature Reviews Genetics |
| 2019 | Avsec | The Kipoi repository accelerates community exchange and reuse of predictive models for genomics | |
| 2019 | Xu | Machine learning and complex biological data | |
| 2019 | Vamathevan | Applications of machine learning in drug discovery and development | |
| 2019 | Preuer | Interpretable Deep Learning in Drug Discovery | |
| 2019 | Polykovskiy | Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models | |
| 2019 | Schneider | Mind and machine in drug design | |
| 2019 | Elton | Deep learning for molecular generation and optimization-a review of the state of the art | |
| 2019 | Topol | High-performance medicine: the convergence of human and artificial intelligence | |
| 2019 | Gromski | How to explore chemical space using algorithms and automation | |
| 2019 | Li | Deep learning in bioinformatics: introduction, application, and perspective in big data era | |
| 2019 | Zachary | Machine-Learning-Assisted Directed Protein Evolution with Combinatorial Libraries | |
| 2019 | Haghighatlari | Advances of Machine Learning in Molecular Modeling and Simulation | |
| 2019 | PLOS | Collection in Machine Learning in Health and Biomedicine | |
| 2019 | Jaganathan | Predicting Splicing from Primary Sequence with Deep Learning | |
| 2019 | He | The practical implementation of artificial intelligence technologies in medicine | |
| 2019 | Kriegescorte | Neural network models and deep learning - a primer for biologists | |
| 2019 | Esteva | A guide to deep learning in healthcare | |
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| 2018 | Yu | Visible Machine Learning for Biomedicine | Cell |
| 2018 | Brown | GuacaMol: Benchmarking Models for de Novo Molecular Design | J. Chem. Inf. Model. |
| 2018 | Sellwood | Artificial intelligence in drug discovery | |
| 2018 | Yu | Artificial intelligence in healthcare | |
| 2018 | Pérez | Simulations meet machine learning in structural biology | |
| 2018 | Zou | A primer on deep learning in genomics | |
| 2018 | Ching | Opportunities and obstacles for deep learning in biology and medicine | |
| 2018 | Greene | Opportunities and obstacles for deep learning in biology and medicine | |
| 2018 | Wainberg | Deep learning in biomedicine | |
| 2018 | Zitnik | Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities | |
| 2018 | Telenti | Deep learning of genomic variation and regulatory network data | |
| 2018 | Yue | Deep Learning for Genomics: A Concise Overview | |
| 2018 | Camacho | Next-Generation Machine Learning for Biological Networks | |
| 2018 | Jung | Machine Learning: Basic Principles | |
| 2018 | Chen | The rise of deep learning in drug discovery. A summary of the latest applications of deep learning to bioactivity and reaction predictions, and image analysis | |
| 2018 | Lo | Machine learning in chemoinformatics and drug discovery | |
| 2018 | Segler | Planning chemical syntheses with deep neural networks and symbolic AI | |
| 2018 | Sundaram | Predicting the clinical impact of human mutation with deep neural networks | |
| 2018 | Zhou | Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk | |
| 2018 | Teschendorff | Avoiding common pitfalls in machine learning omic data science | |
| 2018 | Colwell | Statistical and machine learning approaches to predicting protein–ligand interactions | |
| 2018 | Yang | Machine learning in protein engineering | |
| 2018 | Coley | Machine Learning in Computer-Aided Synthesis Planning | |
| 2018 | Goh | Deep Learning for Computational Chemistry | |
| 2018 | Wu | MoleculeNet: a benchmark for molecular machine learning | |
| 2018 | Salim | Synthetic Patient Generation: A Deep Learning Approach Using Variational Autoencoders | |
| 2018 | Butler | Machine learning for molecular and materials science | |
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| 2017 | Altae-Tran | Low Data Drug Discovery with One-Shot Learning. Learning with little data in drug discovery | |
| 2017 | Ransundar | Is Multitask Deep Learning Practical for Pharma? | |
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| 2016 | Angermueller | Deep learning for computational biology | |
| 2016 | Mamoshina | Applications of Deep Learning in Biomedicine | |
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| 2015 | Park | Deep learning for regulatory genomics | |
| 2015 | LeCun | Deep learning | |