David Eramian
Impact in
- Molecular Biology top 1%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Receptor Mechanisms and Signaling
- Ion channel regulation and function
- Structural Biology top 5%
Papers in
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- Enzyme Structure and Function 6
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- Protein Structure and Dynamics 6
- Glycosylation and Glycoproteins Research 3
- Machine Learning in Bioinformatics 2
- Ion channel regulation and function 1
- Co-authors
- Andrej SăliMin‐Yi ShenNarayanan EswarBen WebbMarc A. Martı́-RenomUrsula PieperM. S. MadhusudhanDamien P. Devos
- Journals
- Protein Science (2 papers)Current Protocols in Protein Science (1 paper)Journal of Cellular Biochemistry (1 paper)Nucleic Acids Research (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesSpainChile
In The Last Decade
David Eramian
8 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Molecular Biology 6.0k
- Structural Biology 68
- Virology 208
- Computational Theory and Mathematics 677
- Biotechnology 346
Countries citing papers authored by David Eramian
This map shows the geographic impact of David Eramian'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 Eramian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Eramian more than expected).
Fields of papers citing papers by David Eramian
This network shows the impact of papers produced by David Eramian. 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 Eramian. The network helps show where David Eramian may publish in the future.
Co-authors
The 25 scholars most cited alongside David Eramian, 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 | 2008 | 126 | |
| 2 | 2008 | 121 | |
| 3 | Protein Structure Modeling with MODELLER Hit paper breakdown → | 2008 | 1510 |
| 4 | 2008 | 91 | |
| 5 | Comparative Protein Structure Modeling Using MODELLER Hit paper breakdown → | 2007 | 2514 |
| 6 | 2006 | 136 | |
| 7 | Comparative Protein Structure Modeling Using Modeller Hit paper breakdown → | 2006 | 3803 |
| 8 | 2004 | 5 |
About David Eramian
David Eramian is a scholar working on Materials Chemistry, Molecular Biology, Genetics, Immunology and Cardiology and Cardiovascular Medicine, having authored 8 papers that have together received 8.3k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Enzyme Structure and Function (6 papers), Glycosylation and Glycoproteins Research (3 papers), Machine Learning in Bioinformatics (2 papers), Mast cells and histamine (1 paper), Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper), Ion channel regulation and function (1 paper) and Nanopore and Nanochannel Transport Studies (1 paper). The work is most often cited by research in Molecular Biology (6.0k citations), Structural Biology (68 citations), Virology (208 citations), Computational Theory and Mathematics (677 citations) and Biotechnology (346 citations). David Eramian has collaborated with scholars based in United States, Spain and Chile. Frequent co-authors include Andrej Săli, Min‐Yi Shen, Narayanan Eswar, Ben Webb, Marc A. Martı́-Renom, Ursula Pieper, M. S. Madhusudhan, Damien P. Devos, Francisco Melo and David T. Barkan. Their work appears in journals such as Protein Science, Current Protocols in Protein Science, Journal of Cellular Biochemistry, Nucleic Acids Research and Proceedings of the National Academy of Sciences.
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.