Christopher Churas
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
- Structural Biology top 10%
Papers in
-
- Bioinformatics and Genomic Networks 9
- Genomics and Phylogenetic Studies 2
- Biomedical Text Mining and Ontologies 1
-
- Topological and Geometric Data Analysis 1
- Co-authors
- Dexter R. Pratt (9 shared papers)Ideker Trey (8 shared papers)Fan Zheng (3 shared papers)Matthew Madany (1 shared paper)Thomas J. Deerinck (1 shared paper)Mark H. Ellisman (2 shared papers)Eric A. Bushong (1 shared paper)Matthias Georg Haberl (1 shared paper)
- Journals
- Bioinformatics (3 papers)PLoS Biology (2 papers)PLoS Computational Biology (1 paper)Nucleic Acids Research (1 paper)Nature Methods (1 paper)
- Partner nations
- United StatesCanadaNigeria
In The Last Decade
Christopher Churas
19 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 108
- Biophysics 101
- Structural Biology 25
- Molecular Biology 469
- Infectious Diseases 124
- Genetics 188
Countries citing papers authored by Christopher Churas
This map shows the geographic impact of Christopher Churas'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 Christopher Churas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Churas more than expected).
Fields of papers citing papers by Christopher Churas
This network shows the impact of papers produced by Christopher Churas. 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 Christopher Churas. The network helps show where Christopher Churas may publish in the future.
Co-authors
The 25 scholars most cited alongside Christopher Churas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 373 | |
| 2 | 2021 | 164 | |
| 3 | 2010 | 140 | |
| 4 | 2018 | 134 | |
| 5 | 2004 | 60 | |
| 6 | 2021 | 50 | |
| 7 | 2018 | 45 | |
| 8 | 2020 | 40 | |
| 9 | 2021 | 40 | |
| 10 | 2021 | 38 | |
| 11 | 2025 | 32 | |
| 12 | 2023 | 27 | |
| 13 | 2021 | 24 | |
| 14 | 2023 | 18 | |
| 15 | 2025 | 17 | |
| 16 | 2024 | 16 | |
| 17 | 2023 | 10 | |
| 18 | 2025 | 2 | |
| 19 | 2017 | 1 | |
| 20 | 2025 | 0 |
About Christopher Churas
Christopher Churas is a scholar working on Molecular Biology, Computational Theory and Mathematics, Structural Biology, Immunology and Biophysics, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (9 papers), interferon and immune responses (2 papers), Genomics and Phylogenetic Studies (2 papers), Topological and Geometric Data Analysis (1 paper), Genomic variations and chromosomal abnormalities (1 paper), Biomedical Text Mining and Ontologies (1 paper), Influenza Virus Research Studies (1 paper) and Biotin and Related Studies (1 paper). The work is most often cited by research in Biophysics (101 citations), Structural Biology (25 citations), Molecular Biology (469 citations), Infectious Diseases (124 citations) and Genetics (188 citations). Christopher Churas has collaborated with scholars based in United States, Canada and Nigeria. Frequent co-authors include Dexter R. Pratt, Ideker Trey, Fan Zheng, Matthew Madany, Thomas J. Deerinck, Mark H. Ellisman, Eric A. Bushong, Matthias Georg Haberl, Daniela Boassa and Sébastien Phan. Their work appears in journals such as Bioinformatics, PLoS Biology, PLoS Computational Biology, Nucleic Acids Research and Nature Methods.
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.