Ed Uberbacher
Impact in
- Plant Science top 10%
- Plant-Microbe Interactions and Immunity
- Mycorrhizal Fungi and Plant Interactions
- Legume Nitrogen Fixing Symbiosis
- Nematode management and characterization studies
- Cell Biology top 10%
- Plant Pathogens and Fungal Diseases
Papers in
-
- Protein Structure and Dynamics 4
- Genetics, Bioinformatics, and Biomedical Research 1
- Machine Learning in Bioinformatics 1
-
- Enzyme Structure and Function 6
- Co-authors
- Dale A. Pelletier (1 shared paper)Zamin K. Yang (1 shared paper)Rytas Vilgalys (1 shared paper)Christopher W. Schadt (1 shared paper)Marilyn Kerley (1 shared paper)Hector F. Castro (1 shared paper)Tatiana V. Karpinets (1 shared paper)Gerald A. Tuskan (1 shared paper)
- Journals
- Journal of Biological Chemistry (3 papers)Molecules (1 paper)Applied and Environmental Microbiology (1 paper)Trends in biotechnology (1 paper)Journal of Physics Conference Series (2 papers)
- Partner nations
- United States
In The Last Decade
Ed Uberbacher
13 papers receiving 575 citations
Peers
Comparison fields: 5 of 76
- Plant Science 345
- Cell Biology 118
- Ecology 117
- Soil Science 42
- Molecular Biology 235
Countries citing papers authored by Ed Uberbacher
This map shows the geographic impact of Ed Uberbacher'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 Ed Uberbacher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ed Uberbacher more than expected).
Fields of papers citing papers by Ed Uberbacher
This network shows the impact of papers produced by Ed Uberbacher. 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 Ed Uberbacher. The network helps show where Ed Uberbacher may publish in the future.
Co-authors
The 25 scholars most cited alongside Ed Uberbacher, 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 | 2011 | 404 | |
| 2 | 1986 | 39 | |
| 3 | 1988 | 35 | |
| 4 | 2015 | 32 | |
| 5 | 1987 | 31 | |
| 6 | 1996 | 26 | |
| 7 | Predicting protein folding classes without overly relying on homology. | 1995 | 13 |
| 8 | 1978 | 5 | |
| 9 | 2008 | 3 | |
| 10 | Reference-based gene model prediction on DNA contigs | 1997 | 1 |
| 11 | 2004 | 1 | |
| 12 | 1995 | 1 | |
| 13 | 2006 | 1 |
About Ed Uberbacher
Ed Uberbacher is a scholar working on Molecular Biology, Materials Chemistry, Cell Biology, Ecology and Information Systems and Management, having authored 13 papers that have together received 592 indexed citations. Recurring topics across this work include Enzyme Structure and Function (6 papers), Protein Structure and Dynamics (4 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Machine Learning in Bioinformatics (1 paper), Metabolism and Genetic Disorders (1 paper), Plant-Microbe Interactions and Immunity (1 paper), Plant Pathogens and Fungal Diseases (1 paper) and X-ray Spectroscopy and Fluorescence Analysis (1 paper). The work is most often cited by research in Plant Science (345 citations), Cell Biology (118 citations), Ecology (117 citations), Soil Science (42 citations) and Molecular Biology (235 citations). Ed Uberbacher has collaborated with scholars based in United States. Frequent co-authors include Dale A. Pelletier, Zamin K. Yang, Rytas Vilgalys, Christopher W. Schadt, Marilyn Kerley, Hector F. Castro, Tatiana V. Karpinets, Gerald A. Tuskan, Mitchel J. Doktycz and Mircea Podar. Their work appears in journals such as Journal of Biological Chemistry, Molecules, Applied and Environmental Microbiology, Trends in biotechnology and Journal of Physics Conference Series.
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.