Brian T. Lee

9.0k citations
8 papers · 1.1k indexed · 1 hit paper · h-index 6
    • Cancer Genomics and Diagnostics 2
    • Genomics and Phylogenetic Studies 5
    • RNA and protein synthesis mechanisms 3
    • RNA modifications and cancer 2
    • Gene expression and cancer classification 2
    • Genomics and Chromatin Dynamics 2
    • vaccines and immunoinformatics approaches 1
  • Genetics top 10%
    • SARS-CoV-2 and COVID-19 Research 1

Brian T. Lee

8 papers receiving 1.1k citations

Hit Papers

The UCSC Genome Browser database: 2019 update5472018202620202023100200300400500

Peers

Brian T. Lee
Comparison fields: 5 of 99
  • Cancer Research 242
  • Molecular Biology 889
  • Genetics 205
  • Immunology 69
  • Infectious Diseases 52
Replace Jairo Navarro Gonzalez with:
Jairo Navarro Gonzalez United States
Galt P Barber United States
Bethan Yates United Kingdom
Aditi K. Narayanan United States
Swarnaseetha Adusumalli Singapore
Shivangi Wani Australia
Forrest Y. Tanaka United States
Damien J. Downes United Kingdom
Xenia Schafer United States
Cricket A. Sloan United States
Brian T. Lee relative to Jairo Navarro Gonzalez United States Jairo Navarro Gonzalez's profile →
Citations per field
00.5×3.2×
Jairo Navarro Gonzalez · 1×
Citations per year

Countries citing papers authored by Brian T. Lee

Since Specialization
Citations

This map shows the geographic impact of Brian T. Lee'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 T. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian T. Lee more than expected).

Fields of papers citing papers by Brian T. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian T. Lee. 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 T. Lee. The network helps show where Brian T. Lee may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Brian T. Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Brian T. Lee Line = papers co-authored together Brian T. Lee links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 20223
2 20222
3 202060
4 2019136
5
The UCSC Genome Browser database: 2019 updatebreakdown →
2018547
6 201623
7 2015317
8 201530

About Brian T. Lee

Brian T. Lee is a scholar working on Cancer Research, Molecular Biology and Infectious Diseases, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), RNA and protein synthesis mechanisms (3 papers), RNA modifications and cancer (2 papers), Cancer Genomics and Diagnostics (2 papers), Gene expression and cancer classification (2 papers), Genomics and Chromatin Dynamics (2 papers), vaccines and immunoinformatics approaches (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Cancer Research (242 citations), Molecular Biology (889 citations) and Genetics (205 citations). Brian T. Lee has collaborated with scholars based in United States and Germany. Frequent co-authors include Angie S. Hinrichs, Maximilian Haeussler, Hiram Clawson, David Haussler, Jairo Navarro Gonzalez, Brian J. Raney, Ann S. Zweig, Kate R. Rosenbloom, Jonathan D. Casper and Galt P Barber. Their work appears in journals such as Nucleic Acids Research, Nature Genetics and Human Mutation.

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.

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