Brian E. Huber

61 papers receiving 2.9k citations

Peers

Brian E. Huber
Comparison fields: 5 of 116
  • Biotechnology 510
  • Genetics 1.2k
  • Small Animals 272
  • Oncology 678
  • Molecular Biology 1.6k
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Annegien Broeks Netherlands
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Citations per year

Countries citing papers authored by Brian E. Huber

Since Specialization
Citations

This map shows the geographic impact of Brian E. Huber'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 E. Huber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian E. Huber more than expected).

Fields of papers citing papers by Brian E. Huber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Brian E. Huber, 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 E. Huber Line = papers co-authored together Brian E. Huber links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994359
2 2008282
3 1991273
4
In vivo antitumor activity of 5-fluorocytosine on human colorectal carcinoma cells genetically modified to express cytosine deaminase.
1993199
5 2008177
6
Enzyme/prodrug gene therapy: comparison of cytosine deaminase/5-fluorocytosine versus thymidine kinase/ganciclovir enzyme/prodrug systems in a human colorectal carcinoma cell line.
1995156
7 1993149
8 1991145
9 1995140
10 1990133
11
Impaired proliferation and tumorigenicity induced by CCAAT/enhancer-binding protein.
199659
12 200958
13 199052
14 198651
15 198845
16 199043
17 200842
18
Enzyme/prodrug gene therapy approach for breast cancer using a recombinant adenovirus expressing Escherichia coli cytosine deaminase.
199742
19 199441
20
Tumorigenicity and transcriptional modulation of c-myc and N-ras oncogenes in a human hepatoma cell line.
198539

About Brian E. Huber

Brian E. Huber is a scholar working on Molecular Biology, Genetics, Oncology, Biotechnology and Cancer Research, having authored 65 papers that have together received 3.1k indexed citations. Recurring topics across this work include Virus-based gene therapy research (15 papers), Cancer Research and Treatments (8 papers), Drug Transport and Resistance Mechanisms (7 papers), CRISPR and Genetic Engineering (6 papers), RNA Interference and Gene Delivery (5 papers), Pharmacogenetics and Drug Metabolism (5 papers), Liver physiology and pathology (4 papers) and CAR-T cell therapy research (4 papers). The work is most often cited by research in Biotechnology (510 citations), Genetics (1.2k citations), Small Animals (272 citations), Oncology (678 citations) and Molecular Biology (1.6k citations). Brian E. Huber has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Elizabeth A. Austin, C A Richards, Steven S. Good, Cynthia A. Richards, Thomas A. Krenitsky, Stephen T. Davis, V C Knick, Peter Kämpfer, Snorri S. Thorgeirsson and Kazutoshi Yamamoto. Their work appears in journals such as INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY, Gene, Annals of the New York Academy of Sciences, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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