David Baker
Impact in
- Molecular Biology top 0.01%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Microbial Metabolic Engineering and Bioproduction
- Machine Learning in Bioinformatics
- Enzyme Catalysis and Immobilization
- Structural Biology top 0.1%
Papers in
-
- Protein Structure and Dynamics 373
- RNA and protein synthesis mechanisms 220
- Machine Learning in Bioinformatics 41
- Glycosylation and Glycoproteins Research 39
- Chemical Synthesis and Analysis 37
-
- Enzyme Structure and Function 275
- Co-authors
- David E. Kim (39 shared papers)Tanja Kortemme (22 shared papers)Brian A. Kuhlman (18 shared papers)Frank DiMaio (60 shared papers)Dylan C. Chivian (14 shared papers)Rhiju Das (14 shared papers)Philip H Bradley (25 shared papers)Barry L. Stoddard (34 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (89 papers)Nature (69 papers)Proteins Structure Function and Bioinformatics (60 papers)Science (55 papers)Journal of Molecular Biology (53 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David Baker
904 papers receiving 106.7k citations
David Baker's Hit Papers
Peers
Comparison fields: 5 of 231
- Molecular Biology 80.3k
- Structural Biology 1.2k
- Materials Chemistry 24.6k
- Virology 2.0k
- Radiology, Nuclear Medicine and Imaging 8.7k
Countries citing papers authored by David Baker
This map shows the geographic impact of David Baker's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Baker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Baker more than expected).
Fields of papers citing papers by David Baker
This network shows the impact of papers produced by David Baker. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Baker. The network helps show where David Baker may publish in the future.
Co-authors
The 25 scholars most cited alongside David Baker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 928 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Accurate prediction of protein structures and interactions using a three-track neural network Hit paper breakdown → | 2021 | 3783 |
| 2 | Protein structure prediction and analysis using the Robetta server Hit paper breakdown → | 2004 | 1727 |
| 3 | Rosetta3 Hit paper breakdown → | 2010 | 1557 |
| 4 | Quantitative reactivity profiling predicts functional cysteines in proteomes Hit paper breakdown → | 2010 | 1456 |
| 5 | Protein Structure Prediction Using Rosetta Hit paper breakdown → | 2004 | 1393 |
| 6 | Design of a Novel Globular Protein Fold with Atomic-Level Accuracy Hit paper breakdown → | 2003 | 1349 |
| 7 | Protein Structure Prediction and Structural Genomics Hit paper breakdown → | 2001 | 1320 |
| 8 | Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and bayesian scoring functions Hit paper breakdown → | 1997 | 1170 |
| 9 | Improving physical realism, stereochemistry, and side‐chain accuracy in homology modeling: Four approaches that performed well in CASP8 Hit paper breakdown → | 2009 | 1170 |
| 10 | De novo design of protein structure and function with RFdiffusion Hit paper breakdown → | 2023 | 1135 |
| 11 | The coming of age of de novo protein design Hit paper breakdown → | 2016 | 1128 |
| 12 | The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design Hit paper breakdown → | 2017 | 1070 |
| 13 | Kemp elimination catalysts by computational enzyme design Hit paper breakdown → | 2008 | 1067 |
| 14 | Robust deep learning–based protein sequence design using ProteinMPNN Hit paper breakdown → | 2022 | 1032 |
| 15 | Improved protein structure prediction using predicted interresidue orientations Hit paper breakdown → | 2020 | 1018 |
| 16 | Predicting protein structures with a multiplayer online game Hit paper breakdown → | 2010 | 1004 |
| 17 | De Novo Computational Design of Retro-Aldol Enzymes Hit paper breakdown → | 2008 | 969 |
| 18 | Protein–Protein Docking with Simultaneous Optimization of Rigid-body Displacement and Side-chain Conformations Hit paper breakdown → | 2003 | 940 |
| 19 | High-Resolution Comparative Modeling with RosettaCM Hit paper breakdown → | 2013 | 882 |
| 20 | Macromolecular Modeling with Rosetta Hit paper breakdown → | 2008 | 812 |
About David Baker
David Baker is a scholar working on Molecular Biology, Materials Chemistry, Radiology, Nuclear Medicine and Imaging, Spectroscopy and Immunology, having authored 928 papers that have together received 109.7k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (373 papers), Enzyme Structure and Function (275 papers), RNA and protein synthesis mechanisms (220 papers), Monoclonal and Polyclonal Antibodies Research (75 papers), Bacteriophages and microbial interactions (59 papers), Machine Learning in Bioinformatics (41 papers), Glycosylation and Glycoproteins Research (39 papers) and Chemical Synthesis and Analysis (37 papers). The work is most often cited by research in Molecular Biology (80.3k citations), Structural Biology (1.2k citations), Materials Chemistry (24.6k citations), Virology (2.0k citations) and Radiology, Nuclear Medicine and Imaging (8.7k citations). David Baker has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include David E. Kim, Tanja Kortemme, Brian A. Kuhlman, Frank DiMaio, Dylan C. Chivian, Rhiju Das, Philip H Bradley, Barry L. Stoddard, Carol A. Rohl and Sergey Ovchinnikov. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature, Proteins Structure Function and Bioinformatics, Science and Journal of Molecular Biology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.