Matthew S. Wiebe

1.2k total citations
26 papers, 911 citations indexed

About

Matthew S. Wiebe is a scholar working on Genetics, Virology and Molecular Biology. According to data from OpenAlex, Matthew S. Wiebe has authored 26 papers receiving a total of 911 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 13 papers in Virology and 10 papers in Molecular Biology. Recurrent topics in Matthew S. Wiebe's work include Virus-based gene therapy research (15 papers), Poxvirus research and outbreaks (13 papers) and Herpesvirus Infections and Treatments (7 papers). Matthew S. Wiebe is often cited by papers focused on Virus-based gene therapy research (15 papers), Poxvirus research and outbreaks (13 papers) and Herpesvirus Infections and Treatments (7 papers). Matthew S. Wiebe collaborates with scholars based in United States, United Kingdom and China. Matthew S. Wiebe's co-authors include Paula Traktman, R. Jeremy Nichols, Angie Rizzino, Tamara K. Nowling, David L. Kelly, L J Miller, Timothy A. Springer, Clinton Jones, Zhigang Wang and Sunil K. Mallanna and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Immunology and PLoS ONE.

In The Last Decade

Matthew S. Wiebe

26 papers receiving 906 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew S. Wiebe United States 16 631 244 162 124 96 26 911
Colin Macaulay United States 17 587 0.9× 283 1.2× 244 1.5× 157 1.3× 137 1.4× 24 1.1k
Chu-Chih Shih United States 10 524 0.8× 209 0.9× 157 1.0× 144 1.2× 32 0.3× 13 945
Laura Doglio United Kingdom 11 332 0.5× 176 0.7× 177 1.1× 65 0.5× 133 1.4× 18 643
Julia M. Rogers United States 13 659 1.0× 157 0.6× 81 0.5× 95 0.8× 38 0.4× 22 955
Ted A. Torrey United States 16 538 0.9× 221 0.9× 100 0.6× 294 2.4× 98 1.0× 22 996
Krassimir Yankulov Canada 17 2.1k 3.4× 176 0.7× 133 0.8× 122 1.0× 119 1.2× 50 2.3k
Susan Kettle United Kingdom 10 399 0.6× 322 1.3× 155 1.0× 127 1.0× 39 0.4× 11 711
Annarita Miccio France 26 1.8k 2.8× 771 3.2× 187 1.2× 141 1.1× 91 0.9× 67 2.5k
S P Goff United States 9 507 0.8× 101 0.4× 412 2.5× 86 0.7× 62 0.6× 12 911
Gregory M. Gilmartin United States 22 2.0k 3.1× 159 0.7× 132 0.8× 89 0.7× 41 0.4× 28 2.1k

Countries citing papers authored by Matthew S. Wiebe

Since Specialization
Citations

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

Fields of papers citing papers by Matthew S. Wiebe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew S. Wiebe. 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 Matthew S. Wiebe. The network helps show where Matthew S. Wiebe may publish in the future.

Co-authorship network of co-authors of Matthew S. Wiebe

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew S. Wiebe. A scholar is included among the top collaborators of Matthew S. Wiebe 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 Matthew S. Wiebe. Matthew S. Wiebe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Smith, Geoffrey L., et al.. (2022). Dysregulation of Cellular VRK1, BAF, and Innate Immune Signaling by the Vaccinia Virus B12 Pseudokinase. Journal of Virology. 96(11). e0039822–e0039822. 2 indexed citations
2.
Martin, Caroline, et al.. (2022). Vaccinia Virus Arrests and Shifts the Cell Cycle. Viruses. 14(2). 431–431. 6 indexed citations
3.
4.
Wang, Zhigang, et al.. (2019). A poxvirus pseudokinase represses viral DNA replication via a pathway antagonized by its paralog kinase. PLoS Pathogens. 15(2). e1007608–e1007608. 20 indexed citations
5.
Wiebe, Matthew S., et al.. (2019). Generation of Vaccinia Virus Gene Deletion Mutants Using Complementing Cell Lines. Methods in molecular biology. 2023. 93–108. 2 indexed citations
6.
Wiebe, Matthew S., et al.. (2016). The Barrier to Autointegration Factor: Interlocking Antiviral Defense with Genome Maintenance. Journal of Virology. 90(8). 3806–3809. 25 indexed citations
7.
Wiebe, Matthew S., et al.. (2015). Barrier to Autointegration Factor (BANF1): interwoven roles in nuclear structure, genome integrity, innate immunity, stress responses and progeria. Current Opinion in Cell Biology. 34. 61–68. 74 indexed citations
8.
Wang, Jianlin, Jeff Alexander, Matthew S. Wiebe, & Clinton Jones. (2014). Bovine herpesvirus 1 productive infection stimulates inflammasome formation and caspase 1 activity. Virus Research. 185. 72–76. 19 indexed citations
9.
10.
Wiebe, Matthew S., et al.. (2013). Barrier to autointegration factor (BAF) inhibits vaccinia virus intermediate transcription in the absence of the viral B1 kinase. Virology. 444(1-2). 363–373. 25 indexed citations
11.
Cox, Jesse L., Sunil K. Mallanna, Briana D. Ormsbee, et al.. (2011). Banf1 is required to maintain the self-renewal of both mouse and human embryonic stem cells. Journal of Cell Science. 124(15). 2654–2665. 42 indexed citations
12.
Wiebe, Matthew S., et al.. (2011). Molecular Characterization of the Host Defense Activity of the Barrier to Autointegration Factor against Vaccinia Virus. Journal of Virology. 85(22). 11588–11600. 35 indexed citations
13.
Wiebe, Matthew S., et al.. (2009). Mice Deficient in the Serine/Threonine Protein Kinase VRK1 Are Infertile Due to a Progressive Loss of Spermatogonia1. Biology of Reproduction. 82(1). 182–193. 41 indexed citations
14.
Wiebe, Matthew S. & Paula Traktman. (2007). Poxviral B1 Kinase Overcomes Barrier to Autointegration Factor, a Host Defense against Virus Replication. Cell Host & Microbe. 1(3). 187–197. 88 indexed citations
15.
Bernadt, Cory T., Tamara K. Nowling, Matthew S. Wiebe, & Angie Rizzino. (2005). NF-Y Behaves as a Bifunctional Transcription Factor That Can Stimulate or Repress the <I>FGF-4</I> Promoter in an Enhancer-Dependent Manner. Gene Expression. 12(3). 193–212. 13 indexed citations
16.
Wiebe, Matthew S., Tamara K. Nowling, & Angie Rizzino. (2003). Identification of Novel Domains within Sox-2 and Sox-11 Involved in Autoinhibition of DNA Binding and Partnership Specificity. Journal of Biological Chemistry. 278(20). 17901–17911. 60 indexed citations
17.
Wiebe, Matthew S., et al.. (2000). Isolation, characterization, and differential expression of the murine Sox-2 promoter. Gene. 246(1-2). 383–393. 57 indexed citations
18.
Nowling, Tamara K., et al.. (2000). Identification of the Transactivation Domain of the Transcription Factor Sox-2 and an Associated Co-activator. Journal of Biological Chemistry. 275(6). 3810–3818. 77 indexed citations
19.
Nelson, Emily V., et al.. (1989). Endogenous retroviruses of continuous cell substrates.. PubMed. 70. 187–91. 7 indexed citations
20.
Miller, L J, Matthew S. Wiebe, & Timothy A. Springer. (1987). Purification and alpha subunit N-terminal sequences of human Mac-1 and p150,95 leukocyte adhesion proteins.. The Journal of Immunology. 138(8). 2381–2383. 38 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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