David Belanger
Google (United States)(US)
Publications by Year
Research Areas
Machine Learning in Bioinformatics, Machine Learning and Algorithms, Genomics and Phylogenetic Studies, RNA and protein synthesis mechanisms, Bioinformatics and Genomic Networks
Most-Cited Works
- → Using deep learning to annotate the protein universe(2022)303 cited
- → ProteInfer, deep neural networks for protein functional inference(2023)173 cited
- Learning Latent Permutations with Gumbel-Sinkhorn Networks(2018)
- → The discovery of novel tartrate-based TNF-α converting enzyme (TACE) inhibitors(2009)28 cited
- → Engineering highly active nuclease enzymes with machine learning and high-throughput screening(2025)16 cited
- → Engineering of highly active and diverse nuclease enzymes by combining machine learning and ultra-high-throughput screening(2024)15 cited
- Marginal Inference in MRFs using Frank-Wolfe(2013)
- → Synthesis and SAR studies of imidazo-[1,2-a]-pyrazine Aurora kinase inhibitors with improved off-target kinase selectivity(2012)11 cited
- → Improving Protein Function Annotation via Unsupervised Pre-training: Robustness, Efficiency, and Insights(2021)11 cited
- → Tuned Fitness Landscapes for Benchmarking Model-Guided Protein Design(2022)8 cited