Eric Martz
- Immunology and Allergy top 0.5%
- Immunology top 1%
- Immune Cell Function and Interaction 18
- T-cell and B-cell Immunology 13
- Immunotherapy and Immune Responses 12
- Molecular Biology top 0.5%
- Protein Structure and Dynamics 7
- Genomics and Phylogenetic Studies 7
- Genetics, Bioinformatics, and Biomedical Research 6
- Cell Biology top 1%
- Cellular Mechanics and Interactions 6
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- Monoclonal and Polyclonal Antibodies Research 17
Eric Martz
77 papers receiving 10.3k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Immunology and Allergy 806
- Immunology 2.4k
- Molecular Biology 6.4k
- Cell Biology 887
- Radiology, Nuclear Medicine and Imaging 1.2k
Countries citing papers authored by Eric Martz
This map shows the geographic impact of Eric Martz'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 Eric Martz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Martz more than expected).
Fields of papers citing papers by Eric Martz
This network shows the impact of papers produced by Eric Martz. 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 Eric Martz. The network helps show where Eric Martz may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eric Martz, 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 | Using evolutionary data to make sense of macromolecules with a “face‐lifted” ConSurfbreakdown → | 2023 | 186 |
| 2 | 2019 | 133 | |
| 3 | ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromoleculesbreakdown → | 2016 | 2170 |
| 4 | 2012 | 10 | |
| 5 | 2011 | 48 | |
| 6 | ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acidsbreakdown → | 2010 | 1494 |
| 7 | 2009 | 177 | |
| 8 | 2008 | 64 | |
| 9 | 2008 | 4 | |
| 10 | ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structuresbreakdown → | 2005 | 1144 |
| 11 | ConSurf: Identification of Functional Regions in Proteinsby Surface-Mapping of Phylogenetic Informationbreakdown → | 2002 | 993 |
| 12 | 1992 | 18 | |
| 13 | 1991 | 36 | |
| 14 | 1988 | 14 | |
| 15 | 1987 | 13 | |
| 16 | 1985 | 20 | |
| 17 | 1985 | 80 | |
| 18 | 1981 | 12 | |
| 19 | 1979 | 18 | |
| 20 | Early steps in specific tumor cell lysis by sensitized mouse T lymphocytes. I. Resolution and characterization. | 1975 | 118 |
About Eric Martz
Eric Martz is a scholar working on Immunology, Immunology and Allergy and Radiology, Nuclear Medicine and Imaging, having authored 77 papers that have together received 10.7k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (18 papers), Monoclonal and Polyclonal Antibodies Research (17 papers), T-cell and B-cell Immunology (13 papers), Immunotherapy and Immune Responses (12 papers), Protein Structure and Dynamics (7 papers), Genomics and Phylogenetic Studies (7 papers), Cellular Mechanics and Interactions (6 papers) and Genetics, Bioinformatics, and Biomedical Research (6 papers). The work is most often cited by research in Immunology and Allergy (806 citations), Immunology (2.4k citations) and Molecular Biology (6.4k citations). Eric Martz has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Tal Pupko, Nir Ben‐Tal, Haim Ashkenazy, Itay Mayrose, Fabian Glaser, Elona Erez, Shiran Abadi, Timothy A. Springer, K. Kürzinger and Meytal Landau. Their work appears in journals such as The Journal of Immunology, Cellular Immunology, Nucleic Acids Research, Advances in experimental medicine and biology and Journal of Cellular Physiology.
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.