Brian Jo
Impact in
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- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- RNA Research and Splicing
- Gene expression and cancer classification
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
Papers in
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- Gene expression and cancer classification 2
- Bioinformatics and Genomic Networks 2
- RNA Research and Splicing 2
- Protein Structure and Dynamics 1
- Gene Regulatory Network Analysis 1
- DNA and Nucleic Acid Chemistry 1
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- Artificial Intelligence in Healthcare 1
- Co-authors
- Teresa Head‐Gordon (1 shared paper)Paul S. Nerenberg (1 shared paper)Ian C. McDowell (2 shared papers)Barbara E. Engelhardt (2 shared papers)Alexis Battle (1 shared paper)Yungil Kim (1 shared paper)Ariel DH Gewirtz (1 shared paper)Ashis Saha (1 shared paper)
- Journals
- The Journal of Physical Chemistry B (1 paper)PLoS Computational Biology (1 paper)Genome Research (1 paper)Nature Communications (1 paper)JMIR AI (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Brian Jo
5 papers receiving 313 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 241
- Spectroscopy 35
- Aging 3
- Atomic and Molecular Physics, and Optics 47
- Materials Chemistry 68
Countries citing papers authored by Brian Jo
This map shows the geographic impact of Brian Jo'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 Brian Jo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Jo more than expected).
Fields of papers citing papers by Brian Jo
This network shows the impact of papers produced by Brian Jo. 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 Brian Jo. The network helps show where Brian Jo may publish in the future.
Co-authors
The 25 scholars most cited alongside Brian Jo, 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 | 2012 | 137 | |
| 2 | 2017 | 104 | |
| 3 | 2013 | 41 | |
| 4 | 2021 | 22 | |
| 5 | 2022 | 12 |
About Brian Jo
Brian Jo is a scholar working on Molecular Biology, Health Information Management, Atomic and Molecular Physics, and Optics, Oncology and Infectious Diseases, having authored 5 papers that have together received 316 indexed citations. Recurring topics across this work include Gene expression and cancer classification (2 papers), Bioinformatics and Genomic Networks (2 papers), RNA Research and Splicing (2 papers), Protein Structure and Dynamics (1 paper), Artificial Intelligence in Healthcare (1 paper), Gene Regulatory Network Analysis (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper) and DNA and Nucleic Acid Chemistry (1 paper). The work is most often cited by research in Molecular Biology (241 citations), Spectroscopy (35 citations), Aging (3 citations), Atomic and Molecular Physics, and Optics (47 citations) and Materials Chemistry (68 citations). Brian Jo has collaborated with scholars based in United States and South Korea. Frequent co-authors include Teresa Head‐Gordon, Paul S. Nerenberg, Ian C. McDowell, Barbara E. Engelhardt, Alexis Battle, Yungil Kim, Ariel DH Gewirtz, Ashis Saha, Chuan Gao and David M. Jablons. Their work appears in journals such as The Journal of Physical Chemistry B, PLoS Computational Biology, Genome Research, Nature Communications and JMIR AI.
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.