Christopher M. Browne

651 total citations
9 papers, 210 citations indexed

About

Christopher M. Browne is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Christopher M. Browne has authored 9 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Cell Biology. Recurrent topics in Christopher M. Browne's work include RNA and protein synthesis mechanisms (5 papers), RNA modifications and cancer (3 papers) and Protein Degradation and Inhibitors (3 papers). Christopher M. Browne is often cited by papers focused on RNA and protein synthesis mechanisms (5 papers), RNA modifications and cancer (3 papers) and Protein Degradation and Inhibitors (3 papers). Christopher M. Browne collaborates with scholars based in United States, South Korea and Russia. Christopher M. Browne's co-authors include Jarrod A. Marto, Scott B. Ficarro, Nathanael S. Gray, Parimal Samir, Andrew J. Link, Ming Sun, Tinghu Zhang, Joachim Frank, Lewis C. Cantley and Zainab M. Doctor and has published in prestigious journals such as Journal of the American Chemical Society, Molecular and Cellular Biology and Analytical Chemistry.

In The Last Decade

Christopher M. Browne

9 papers receiving 206 citations

Peers

Christopher M. Browne
Kelly M. George United States
Alan T. Henley United Kingdom
Hendrik Falk Australia
Emma J. Jones United Kingdom
Allison M. Roberts United States
Gregory B. Craven United Kingdom
Gary Fairley United Kingdom
Andrew Plater United Kingdom
Y. Carrasco United States
Zhizhou Fang Germany
Kelly M. George United States
Christopher M. Browne
Citations per year, relative to Christopher M. Browne Christopher M. Browne (= 1×) peers Kelly M. George

Countries citing papers authored by Christopher M. Browne

Since Specialization
Citations

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

Fields of papers citing papers by Christopher M. Browne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher M. Browne. 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 Christopher M. Browne. The network helps show where Christopher M. Browne may publish in the future.

Co-authorship network of co-authors of Christopher M. Browne

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

All Works

9 of 9 papers shown
1.
Link, Andrew J., Xinnan Niu, Connie M. Weaver, et al.. (2020). Targeted Identification of Protein Interactions in Eukaryotic mRNA Translation. PROTEOMICS. 20(7). e1900177–e1900177. 2 indexed citations
2.
Sun, Ming, Wen Li, Parimal Samir, et al.. (2020). A Time‐Resolved Cryo‐EM Study of Saccharomyces cerevisiae 80S Ribosome Protein Composition in Response to a Change in Carbon Source. PROTEOMICS. 21(2). e2000125–e2000125. 8 indexed citations
3.
Gurbani, Deepak, Guangyan Du, Robert A. Everley, et al.. (2019). Leveraging Compound Promiscuity to Identify Targetable Cysteines within the Kinome. Cell chemical biology. 26(6). 818–829.e9. 51 indexed citations
4.
Ferguson, Fleur M., Zainab M. Doctor, Scott B. Ficarro, et al.. (2019). Discovery of Covalent CDK14 Inhibitors with Pan-TAIRE Family Specificity. Cell chemical biology. 26(6). 804–817.e12. 19 indexed citations
5.
Browne, Christopher M., Baishan Jiang, Scott B. Ficarro, et al.. (2018). A Chemoproteomic Strategy for Direct and Proteome-Wide Covalent Inhibitor Target-Site Identification. Journal of the American Chemical Society. 141(1). 191–203. 56 indexed citations
6.
Gerbasi, Vincent R., Christopher M. Browne, Parimal Samir, et al.. (2018). Critical Role for Saccharomyces cerevisiae Asc1p in Translational Initiation at Elevated Temperatures. PROTEOMICS. 18(23). e1800208–e1800208. 4 indexed citations
7.
Samir, Parimal, Christopher M. Browne, Rahul, et al.. (2018). Identification of Changing Ribosome Protein Compositions using Mass Spectrometry. PROTEOMICS. 18(20). e1800217–e1800217. 33 indexed citations
8.
Ficarro, Scott B., Christopher M. Browne, Tinghu Zhang, et al.. (2016). Leveraging Gas-Phase Fragmentation Pathways for Improved Identification and Selective Detection of Targets Modified by Covalent Probes. Analytical Chemistry. 88(24). 12248–12254. 26 indexed citations
9.
Browne, Christopher M., Parimal Samir, J. Scott Fites, Seth A. Villarreal, & Andrew J. Link. (2012). The Yeast Eukaryotic Translation Initiation Factor 2B Translation Initiation Complex Interacts with the Fatty Acid Synthesis Enzyme YBR159W and Endoplasmic Reticulum Membranes. Molecular and Cellular Biology. 33(5). 1041–1056. 11 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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