Ashley E. Modell
Impact in
-
- CRISPR and Genetic Engineering
- Chemical Synthesis and Analysis
- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- Protein Structure and Dynamics
- Advanced biosensing and bioanalysis techniques
Papers in
-
- Innovation and Socioeconomic Development 2
-
- Computational Drug Discovery Methods 3
- Co-authors
- Paramjit S. Arora (4 shared papers)Amit Choudhary (6 shared papers)Tuan M. Nguyen (2 shared papers)Donghyun Lim (2 shared papers)Vedagopuram Sreekanth (1 shared paper)Yingkai Zhang (2 shared papers)Veronika M. Shoba (4 shared papers)Sophia Lai (1 shared paper)
- Journals
- Journal of the American Chemical Society (2 papers)Trends in Pharmacological Sciences (2 papers)Molecular Metabolism (1 paper)Cell chemical biology (1 paper)Current Opinion in Chemical Biology (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Ashley E. Modell
11 papers receiving 364 citations
Peers
Comparison fields: 5 of 63
- Molecular Biology 290
- Business and International Management 8
- Aging 5
- Computational Theory and Mathematics 41
- Microbiology 12
Countries citing papers authored by Ashley E. Modell
This map shows the geographic impact of Ashley E. Modell'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 Ashley E. Modell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashley E. Modell more than expected).
Fields of papers citing papers by Ashley E. Modell
This network shows the impact of papers produced by Ashley E. Modell. 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 Ashley E. Modell. The network helps show where Ashley E. Modell may publish in the future.
Co-authors
The 24 scholars most cited alongside Ashley E. Modell, 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 | 2016 | 142 | |
| 2 | 2021 | 76 | |
| 3 | 2017 | 41 | |
| 4 | 2022 | 38 | |
| 5 | 2021 | 37 | |
| 6 | 2022 | 16 | |
| 7 | 2020 | 16 | |
| 8 | 2022 | 10 | |
| 9 | 2020 | 3 | |
| 10 | 2022 | 1 | |
| 11 | 2020 | 1 |
About Ashley E. Modell
Ashley E. Modell is a scholar working on Business and International Management, Computational Theory and Mathematics, Molecular Biology, Physiology and Public Health, Environmental and Occupational Health, having authored 11 papers that have together received 381 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (3 papers), Computational Drug Discovery Methods (3 papers), Pancreatic function and diabetes (2 papers), Innovation and Socioeconomic Development (2 papers), Mosquito-borne diseases and control (2 papers), Chemical Synthesis and Analysis (2 papers), Ubiquitin and proteasome pathways (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). The work is most often cited by research in Molecular Biology (290 citations), Business and International Management (8 citations), Aging (5 citations), Computational Theory and Mathematics (41 citations) and Microbiology (12 citations). Ashley E. Modell has collaborated with scholars based in United States and China. Frequent co-authors include Paramjit S. Arora, Amit Choudhary, Tuan M. Nguyen, Donghyun Lim, Vedagopuram Sreekanth, Yingkai Zhang, Veronika M. Shoba, Sophia Lai, David W. Rooklin and Haotian Li. Their work appears in journals such as Journal of the American Chemical Society, Trends in Pharmacological Sciences, Molecular Metabolism, Cell chemical biology and Current Opinion in Chemical 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.