Brian Teague

4.0k total citations
9 papers, 713 citations indexed

About

Brian Teague is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Brian Teague has authored 9 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Plant Science. Recurrent topics in Brian Teague's work include CRISPR and Genetic Engineering (5 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers) and Gene Regulatory Network Analysis (2 papers). Brian Teague is often cited by papers focused on CRISPR and Genetic Engineering (5 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers) and Gene Regulatory Network Analysis (2 papers). Brian Teague collaborates with scholars based in United States, Italy and Spain. Brian Teague's co-authors include Ron Weiss, Tasuku Kitada, Breanna DiAndreth, Patrick Guye, Evan E. Eichler, Jeffrey M. Kidd, David C. Schwartz, Tyler Wagner, Brian Dobosh and Ely Porter and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Brian Teague

9 papers receiving 693 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Brian Teague United States	8	586	192	128	88	61	9	713
Alexander S. Garruss United States	10	1.1k 2.0×	175 0.9×	58 0.5×	60 0.7×	40 0.7×	12	1.3k
Daniel J. Wiegand United States	6	1.3k 2.2×	204 1.1×	44 0.3×	89 1.0×	74 1.2×	6	1.4k
Andrew H. Ng United States	11	690 1.2×	120 0.6×	74 0.6×	34 0.4×	29 0.5×	14	767
Tasuku Kitada United States	13	1.1k 1.9×	179 0.9×	75 0.6×	63 0.7×	131 2.1×	17	1.3k
Lior Nissim Israel	9	628 1.1×	104 0.5×	56 0.4×	57 0.6×	92 1.5×	14	723
Ryan J. Cecchi United States	5	770 1.3×	143 0.7×	51 0.4×	56 0.6×	76 1.2×	7	865
Ty C. Voss United States	11	357 0.6×	140 0.7×	57 0.4×	169 1.9×	66 1.1×	15	658
Peter Lotfy United States	5	1.1k 1.9×	149 0.8×	30 0.2×	77 0.9×	40 0.7×	6	1.2k
Daniel Scherly Switzerland	14	1.2k 2.1×	85 0.4×	122 1.0×	93 1.1×	31 0.5×	28	1.4k
Tony P. Huang United States	11	1.2k 2.1×	342 1.8×	24 0.2×	95 1.1×	59 1.0×	11	1.3k

Countries citing papers authored by Brian Teague

Since Specialization

Citations

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

Fields of papers citing papers by Brian Teague

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Teague

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Teague. A scholar is included among the top collaborators of Brian Teague based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Brian Teague. Brian Teague is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Beal, Jacob, et al.. (2022). Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks. ACS Synthetic Biology. 11(3). 1196–1207. 5 indexed citations

2.

Bepler, Tristan, et al.. (2021). An engineered protein-phosphorylation toggle network with implications for endogenous network discovery. Science. 373(6550). 27 indexed citations

3.

Li, Yingzhong, Brian Teague, Yuan Zhang, et al.. (2019). In vitro evolution of enhanced RNA replicons for immunotherapy. Scientific Reports. 9(1). 6932–6932. 55 indexed citations

4.

Wagner, Tyler, Brian Teague, Xin Zhang, et al.. (2018). Small-molecule-based regulation of RNA-delivered circuits in mammalian cells. Nature Chemical Biology. 14(11). 1043–1050. 53 indexed citations

5.

Gaidukov, Leonid, Liliana Wróblewska, Brian Teague, et al.. (2018). A multi-landing pad DNA integration platform for mammalian cell engineering. Nucleic Acids Research. 46(8). 4072–4086. 115 indexed citations

6.

Kitada, Tasuku, Breanna DiAndreth, Brian Teague, & Ron Weiss. (2018). Programming gene and engineered-cell therapies with synthetic biology. Science. 359(6376). 192 indexed citations

7.

Teague, Brian, Patrick Guye, & Ron Weiss. (2016). Synthetic Morphogenesis. Cold Spring Harbor Perspectives in Biology. 8(9). a023929–a023929. 67 indexed citations

8.

Antonacci, Francesca, Jeffrey M. Kidd, Tomàs Marquès‐Bonet, et al.. (2010). A large and complex structural polymorphism at 16p12.1 underlies microdeletion disease risk. Nature Genetics. 42(9). 745–750. 73 indexed citations

9.

Teague, Brian, Michael S. Waterman, Steven Goldstein, et al.. (2010). High-resolution human genome structure by single-molecule analysis. Proceedings of the National Academy of Sciences. 107(24). 10848–10853. 126 indexed citations

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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