David Baker

146.6k citations
790 papers · 88.0k · 83 hit papers · h-index 158

Impact in

    • Protein Structure and Dynamics
    • RNA and protein synthesis mechanisms
    • Microbial Metabolic Engineering and Bioproduction
    • Machine Learning in Bioinformatics
    • Enzyme Catalysis and Immobilization

Papers in

    • Protein Structure and Dynamics 348
    • RNA and protein synthesis mechanisms 201
    • Glycosylation and Glycoproteins Research 38
    • Machine Learning in Bioinformatics 38
    • Enzyme Structure and Function 262

David Baker

768 papers receiving 86.6k citations

David Baker's Hit Papers

De novo design of luciferases using deep learning 2023 · 279 citations
2790+3+6Years since publication2505007501000

Peers

David Baker
Comparison fields: 5 of 226
  • Molecular Biology 67.0k
  • Structural Biology 988
  • Materials Chemistry 21.8k
  • Spectroscopy 5.5k
  • Virology 1.4k
Replace Andrej Šali with:
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Christopher M. Dobson United Kingdom
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David Baker relative to Andrej Šali United States Andrej Šali's profile →
Citations per field
00.5×4.0×
Andrej Šali · 1×
Citations per year

Countries citing papers authored by David Baker

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with David Baker Line = papers co-authored together David Baker links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 790 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Protein structure prediction and analysis using the Robetta server
Hit paper breakdown →
20041629
2
Quantitative reactivity profiling predicts functional cysteines in proteomes
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20101371
3
Contact order, transition state placement and the refolding rates of single domain proteins 1 1Edited by P. E. Wright
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19981285
4
Protein Structure Prediction Using Rosetta
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20041283
5
Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
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20031270
6
Protein Structure Prediction and Structural Genomics
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20011228
7
Improving physical realism, stereochemistry, and side‐chain accuracy in homology modeling: Four approaches that performed well in CASP8
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20091122
8
Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and bayesian scoring functions
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19971096
9
The coming of age of de novo protein design
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20161038
10
Kemp elimination catalysts by computational enzyme design
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2008988
11
The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design
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2017977
12
Improved protein structure prediction using predicted interresidue orientations
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2020950
13
De Novo Computational Design of Retro-Aldol Enzymes
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2008903
14
Protein–Protein Docking with Simultaneous Optimization of Rigid-body Displacement and Side-chain Conformations
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2003886
15
Predicting protein structures with a multiplayer online game
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2010877
16
High-Resolution Comparative Modeling with RosettaCM
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2013824
17
Macromolecular Modeling with Rosetta
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2008754
18
Computational Design of an Enzyme Catalyst for a Stereoselective Bimolecular Diels-Alder Reaction
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2010696
19
Consistent blind protein structure generation from NMR chemical shift data
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2008675
20
Native protein sequences are close to optimal for their structures
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2000663

About David Baker

David Baker is a scholar working on Molecular Biology, Materials Chemistry, Radiology, Nuclear Medicine and Imaging, Spectroscopy and Ecology, having authored 790 papers that have together received 88.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (348 papers), Enzyme Structure and Function (262 papers), RNA and protein synthesis mechanisms (201 papers), Monoclonal and Polyclonal Antibodies Research (62 papers), Bacteriophages and microbial interactions (49 papers), Glycosylation and Glycoproteins Research (38 papers), Machine Learning in Bioinformatics (38 papers) and Mass Spectrometry Techniques and Applications (31 papers). The work is most often cited by research in Molecular Biology (67.0k citations), Structural Biology (988 citations), Materials Chemistry (21.8k citations), Spectroscopy (5.5k citations) and Virology (1.4k citations). David Baker has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include David E. Kim, Kim T. Simons, Tanja Kortemme, Brian Kuhlman, Frank DiMaio, Dylan Chivian, Rhiju Das, Barry Stoddard, Sergey Ovchinnikov and Carol A. Rohl. Their work appears in journals such as Proceedings of the National Academy of Sciences, Proteins Structure Function and Bioinformatics, Journal of Molecular Biology, Nature and Protein Science.

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.

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