Michelle DeWitt
Impact in
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- Protein Structure and Dynamics
- Enzyme Catalysis and Immobilization
- Microbial Metabolic Engineering and Bioproduction
- bioluminescence and chemiluminescence research
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
Papers in
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- Biochemical and Structural Characterization 1
- Ubiquitin and proteasome pathways 1
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- Smoking Behavior and Cessation 2
- Co-authors
- Hsien‐Wei Yeh (1 shared paper)Declan Evans (1 shared paper)K. N. Houk (1 shared paper)David Baker (2 shared papers)Christoffer Norn (1 shared paper)Yakov Kipnis (1 shared paper)Samuel J. Pellock (1 shared paper)Ivan Anishchenko (1 shared paper)
- Journals
- Implementation Science (2 papers)Translational Behavioral Medicine (1 paper)Infection Control and Hospital Epidemiology (1 paper)Proceedings of the National Academy of Sciences (1 paper)Nature (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Michelle DeWitt
6 papers receiving 354 citations
Michelle DeWitt's Hit Papers
Peers
Comparison fields: 5 of 82
- Applied Microbiology and Biotechnology 7
- Molecular Biology 207
- Health Information Management 9
- Biotechnology 15
- Structural Biology 2
Countries citing papers authored by Michelle DeWitt
This map shows the geographic impact of Michelle DeWitt'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 Michelle DeWitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelle DeWitt more than expected).
Fields of papers citing papers by Michelle DeWitt
This network shows the impact of papers produced by Michelle DeWitt. 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 Michelle DeWitt. The network helps show where Michelle DeWitt may publish in the future.
Co-authors
The 25 scholars most cited alongside Michelle DeWitt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | De novo design of luciferases using deep learning Hit paper breakdown → | 2023 | 279 |
| 2 | 2017 | 33 | |
| 3 | 2019 | 17 | |
| 4 | 2020 | 10 | |
| 5 | 2015 | 10 | |
| 6 | 2022 | 9 | |
| 7 | 2020 | 0 | |
| 8 | Teens Acting Against Violence (TAAV) Program Evaluation | 2015 | 0 |
About Michelle DeWitt
Michelle DeWitt is a scholar working on Molecular Biology, Physiology, Surgery, Cellular and Molecular Neuroscience and Toxicology, having authored 8 papers that have together received 358 indexed citations. Recurring topics across this work include Smoking Behavior and Cessation (2 papers), Youth Development and Social Support (1 paper), Antibiotic Use and Resistance (1 paper), Spinal Hematomas and Complications (1 paper), Spinal Dysraphism and Malformations (1 paper), Biochemical and Structural Characterization (1 paper), Ubiquitin and proteasome pathways (1 paper) and Bacterial Identification and Susceptibility Testing (1 paper). The work is most often cited by research in Applied Microbiology and Biotechnology (7 citations), Molecular Biology (207 citations), Health Information Management (9 citations), Biotechnology (15 citations) and Structural Biology (2 citations). Michelle DeWitt has collaborated with scholars based in United States and China. Frequent co-authors include Hsien‐Wei Yeh, Declan Evans, K. N. Houk, David Baker, Christoffer Norn, Yakov Kipnis, Samuel J. Pellock, Ivan Anishchenko, Longxing Cao and Justas Dauparas. Their work appears in journals such as Implementation Science, Translational Behavioral Medicine, Infection Control and Hospital Epidemiology, Proceedings of the National Academy of Sciences and Nature.
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.