Tom S. Wehrman

1.9k total citations
27 papers, 1.5k citations indexed

About

Tom S. Wehrman is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Tom S. Wehrman has authored 27 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 11 papers in Cellular and Molecular Neuroscience and 7 papers in Oncology. Recurrent topics in Tom S. Wehrman's work include Receptor Mechanisms and Signaling (12 papers), Neuropeptides and Animal Physiology (8 papers) and Cytokine Signaling Pathways and Interactions (5 papers). Tom S. Wehrman is often cited by papers focused on Receptor Mechanisms and Signaling (12 papers), Neuropeptides and Animal Physiology (8 papers) and Cytokine Signaling Pathways and Interactions (5 papers). Tom S. Wehrman collaborates with scholars based in United States, United Kingdom and Germany. Tom S. Wehrman's co-authors include Helen M. Blau, K. Christopher García, Daniel L. Bassoni, Xiaolin He, George L. Sen, Robert F. Balint, J H Her, Benjamin Kleaveland, William J. Raab and Jason W. Myers and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Tom S. Wehrman

26 papers receiving 1.5k citations

Peers

Tom S. Wehrman

CMN

ONCOL

IMMUN

RNMI

Jiansong Luo United States

Laura E. Kilpatrick United Kingdom

Kouki Kawakami Japan

Jianyun Huang United States

Zhi-jie Jey Cheng United States

Andrew Freywald Canada

Jiefei Tong Canada

Joseph Pearlberg United States

Serge Moffett Canada

Tony Pawson Canada

Jiansong Luo United States

Tom S. Wehrman

913 ×0.8

340 ×0.6

CMN

431 ×1.6

ONCOL

373 ×1.7

IMMUN

115 ×0.6

RNMI

Citations per year, relative to Tom S. Wehrman Tom S. Wehrman (= 1×) peers Jiansong Luo

Countries citing papers authored by Tom S. Wehrman

Since Specialization

Citations

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

Fields of papers citing papers by Tom S. Wehrman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom S. Wehrman

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

All Works

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20 of 20 papers shown

Bassoni, Daniel L., András Szabó, Haleli Sharir, et al.. (2018). A Pharmacochaperone-Based High-Throughput Screening Assay for the Discovery of Chemical Probes of Orphan Receptors. Assay and Drug Development Technologies. 16(7). 384–396. 3 indexed citations

Moraga, Ignacio, Jamie B. Spangler, Juan L. Mendoza, et al.. (2017). Synthekines are surrogate cytokine and growth factor agonists that compel signaling through non-natural receptor dimers. eLife. 6. 53 indexed citations

Ho, Chia Chi M., Akanksha Chhabra, Philipp Starkl, et al.. (2017). Decoupling the Functional Pleiotropy of Stem Cell Factor by Tuning c-Kit Signaling. Cell. 168(6). 1041–1052.e18. 52 indexed citations

Horecka, Joe, et al.. (2015). Rapid, Antibody-Free Detection of Recombinant Proteins on Blots Using Enzyme Fragment Complementation. Methods in molecular biology. 1314. 51–61. 1 indexed citations

Burford, Neil T., Kathryn E. Livingston, Meritxell Canals, et al.. (2015). Discovery, Synthesis, and Molecular Pharmacology of Selective Positive Allosteric Modulators of the δ-Opioid Receptor. Journal of Medicinal Chemistry. 58(10). 4220–4229. 60 indexed citations

Moraga, Ignacio, Gerlinde Wernig, Stephan Wilmes, et al.. (2015). Tuning Cytokine Receptor Signaling by Re-orienting Dimer Geometry with Surrogate Ligands. Cell. 160(6). 1196–1208. 123 indexed citations

Burford, Neil T., Tom S. Wehrman, Daniel L. Bassoni, et al.. (2014). Identification of Selective Agonists and Positive Allosteric Modulators for µ- and δ-Opioid Receptors from a Single High-Throughput Screen. SLAS DISCOVERY. 19(9). 1255–1265. 28 indexed citations

Wehrman, Tom S., et al.. (2013). EphB4 Cellular Kinase Activity Assayed Using an Enzymatic Protein Interaction System. Assay and Drug Development Technologies. 11(4). 237–243. 1 indexed citations

Southern, C., Jennifer M. Cook, Debra L. Taylor, et al.. (2013). Screening β-Arrestin Recruitment for the Identification of Natural Ligands for Orphan G-Protein–Coupled Receptors. SLAS DISCOVERY. 18(5). 599–609. 150 indexed citations

10.

Rajagopal, Sudarshan, Daniel L. Bassoni, James J. Campbell, et al.. (2013). Biased Agonism as a Mechanism for Differential Signaling by Chemokine Receptors. Journal of Biological Chemistry. 288(49). 35039–35048. 108 indexed citations

11.

Bassoni, Daniel L., et al.. (2012). Measurements of β-Arrestin Recruitment to Activated Seven Transmembrane Receptors Using Enzyme Complementation. Methods in molecular biology. 897. 181–203. 37 indexed citations

12.

Bassoni, Daniel L., et al.. (2012). Characterization of G-Protein Coupled Receptor Modulators Using Homogeneous cAMP Assays. Methods in molecular biology. 897. 171–180. 4 indexed citations

13.

Maguire, Janet J., Rhoda E. Kuc, Victoria R. Pell, et al.. (2012). Comparison of human ETA and ETB receptor signalling via G-protein and β-arrestin pathways. Life Sciences. 91(13-14). 544–549. 26 indexed citations

14.

Degenfeld, Georges von, Tom S. Wehrman, & Helen M. Blau. (2009). Imaging β-Galactosidase Activity In Vivo Using Sequential Reporter-Enzyme Luminescence. Methods in molecular biology. 574. 249–259. 5 indexed citations

15.

Zhao, Xiaoning, Keith R. Olson, Kun Peng, et al.. (2008). A Homogeneous Enzyme Fragment Complementation-Based β-Arrestin Translocation Assay for High-Throughput Screening of G-Protein-Coupled Receptors. SLAS DISCOVERY. 13(8). 737–747. 56 indexed citations

16.

Wehrman, Tom S., et al.. (2007). Structural and Mechanistic Insights into Nerve Growth Factor Interactions with the TrkA and p75 Receptors. Neuron. 53(1). 25–38. 224 indexed citations

17.

Wehrman, Tom S., et al.. (2006). A system for quantifying dynamic protein interactions defines a role for Herceptin in modulating ErbB2 interactions. Proceedings of the National Academy of Sciences. 103(50). 19063–19068. 69 indexed citations

18.

Sen, George L., Tom S. Wehrman, & Helen M. Blau. (2005). mRNA translation is not a prerequisite for small interfering RNA-mediated mRNA cleavage. Differentiation. 73(6). 287–293. 12 indexed citations

19.

Wehrman, Tom S., et al.. (2005). Enzymatic detection of protein translocation. Nature Methods. 2(7). 521–527. 49 indexed citations

20.

Sen, George L., Tom S. Wehrman, Jason W. Myers, & Helen M. Blau. (2004). Restriction enzyme–generated siRNA (REGS) vectors and libraries. Nature Genetics. 36(2). 183–189. 114 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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