Ming C. Hammond

3.6k total citations · 1 hit paper
58 papers, 2.8k citations indexed

About

Ming C. Hammond is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Ming C. Hammond has authored 58 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 20 papers in Genetics and 7 papers in Ecology. Recurrent topics in Ming C. Hammond's work include RNA and protein synthesis mechanisms (32 papers), Bacterial Genetics and Biotechnology (19 papers) and RNA modifications and cancer (15 papers). Ming C. Hammond is often cited by papers focused on RNA and protein synthesis mechanisms (32 papers), Bacterial Genetics and Biotechnology (19 papers) and RNA modifications and cancer (15 papers). Ming C. Hammond collaborates with scholars based in United States, Germany and Russia. Ming C. Hammond's co-authors include Colleen A. Kellenberger, Stephen C. Wilson, Yichi Su, Ronald R. Breaker, Mamoru Hyodo, Yoshihiro Hayakawa, Elie J. Diner, Kathryn M. Monroe, Russell E. Vance and Dara Burdette and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ming C. Hammond

57 papers receiving 2.8k citations

Hit Papers

The Innate Immune DNA Sensor cGAS Produces a Noncanonical... 2013 2026 2017 2021 2013 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming C. Hammond United States 26 2.2k 705 536 320 190 58 2.8k
Christian Berens Germany 28 1.9k 0.8× 288 0.4× 672 1.3× 324 1.0× 243 1.3× 99 2.9k
Colleen A. Kellenberger United States 14 1.1k 0.5× 592 0.8× 200 0.4× 276 0.9× 149 0.8× 18 1.6k
Daniel Gillet France 27 971 0.4× 691 1.0× 222 0.4× 343 1.1× 66 0.3× 77 2.2k
Kristian Schweimer Germany 30 2.0k 0.9× 272 0.4× 657 1.2× 138 0.4× 278 1.5× 86 3.1k
Puthupparampil V. Scaria United States 25 1.7k 0.8× 248 0.4× 334 0.6× 88 0.3× 91 0.5× 41 2.1k
Alejandro P. Heuck United States 24 1.3k 0.6× 349 0.5× 225 0.4× 455 1.4× 191 1.0× 33 2.2k
Tomas Moks Sweden 22 2.1k 0.9× 260 0.4× 426 0.8× 191 0.6× 325 1.7× 30 2.7k
Aline Desmyter France 28 2.4k 1.1× 634 0.9× 312 0.6× 159 0.5× 486 2.6× 37 3.5k
Christoph Rademacher Germany 29 1.7k 0.8× 726 1.0× 145 0.3× 246 0.8× 130 0.7× 88 2.5k
Catharina Steentoft Denmark 21 2.3k 1.0× 804 1.1× 171 0.3× 128 0.4× 69 0.4× 26 2.9k

Countries citing papers authored by Ming C. Hammond

Since Specialization
Citations

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

Fields of papers citing papers by Ming C. Hammond

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming C. Hammond. 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 Ming C. Hammond. The network helps show where Ming C. Hammond may publish in the future.

Co-authorship network of co-authors of Ming C. Hammond

This figure shows the co-authorship network connecting the top 25 collaborators of Ming C. Hammond. A scholar is included among the top collaborators of Ming C. Hammond 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 Ming C. Hammond. Ming C. Hammond 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.
Jadhav, Rohit G., et al.. (2024). Development of Malate Biosensor-Containing Hydrogels and Living Cell-Based Sensors. International Journal of Molecular Sciences. 25(20). 11098–11098. 1 indexed citations
3.
Bellone, Rebecca R., Jun Tanaka, R. Bryan Sutton, et al.. (2023). A de novo 2.3 kb structural variant in MITF explains a novel splashed white phenotype in a Thoroughbred family. Animal Genetics. 54(6). 752–762. 3 indexed citations
4.
Poon, Raymond, et al.. (2022). In Vivo Detection of Cyclic-di-AMP in Staphylococcus aureus. ACS Omega. 7(36). 32749–32753. 7 indexed citations
5.
Hallberg, Zachary F., et al.. (2022). Production of 3′,3′-cGAMP by a Bdellovibrio bacteriovorus promiscuous GGDEF enzyme, Bd0367, regulates exit from prey by gliding motility. PLoS Genetics. 18(5). e1010164–e1010164. 12 indexed citations
6.
Su, Yichi & Ming C. Hammond. (2020). RNA-based fluorescent biosensors for live cell imaging of small molecules and RNAs. Current Opinion in Biotechnology. 63. 157–166. 70 indexed citations
7.
Giegé, Philippe, Laurence Drouard, Dimitri Heintz, et al.. (2020). Synthetic biological circuit tested in spaceflight. Life Sciences in Space Research. 28. 57–65. 3 indexed citations
8.
Park, Namje, et al.. (2019). Second messengers and divergent HD‐GYP phosphodiesterases regulate 3′,3′‐cGAMP signaling. Molecular Microbiology. 113(1). 222–236. 25 indexed citations
9.
Jia, Guifang, et al.. (2018). Designing fluorescent biosensors using circular permutations of riboswitches. Methods. 143. 102–109. 22 indexed citations
10.
Yeo, Jongchan, et al.. (2017). Live Flow Cytometry Analysis of c-di-GMP Levels in Single Cell Populations. Methods in molecular biology. 1657. 111–130. 4 indexed citations
11.
Hallberg, Zachary F., et al.. (2016). Hybrid promiscuous (Hypr) GGDEF enzymes produce cyclic AMP-GMP (3′, 3′-cGAMP). Proceedings of the National Academy of Sciences. 113(7). 1790–1795. 57 indexed citations
12.
Kellenberger, Colleen A., Jade Sales-Lee, Yu‐Chen Pan, et al.. (2015). A minimalist biosensor: Quantitation of cyclic di-GMP using the conformational change of a riboswitch aptamer. RNA Biology. 12(11). 1189–1197. 25 indexed citations
13.
Kellenberger, Colleen A., Zachary F. Hallberg, & Ming C. Hammond. (2015). Live Cell Imaging Using Riboswitch-Spinach tRNA Fusions as Metabolite-Sensing Fluorescent Biosensors. Methods in molecular biology. 1316. 87–103. 16 indexed citations
14.
Kellenberger, Colleen A., Chen Chen, Aaron T. Whiteley, Daniel A. Portnoy, & Ming C. Hammond. (2015). RNA-Based Fluorescent Biosensors for Live Cell Imaging of Second Messenger Cyclic di-AMP. Journal of the American Chemical Society. 137(20). 6432–6435. 98 indexed citations
15.
Wilson, Stephen C., et al.. (2014). A neutral pH thermal hydrolysis method for quantification of structured RNAs. RNA. 20(7). 1153–1160. 25 indexed citations
16.
Kellenberger, Colleen A. & Ming C. Hammond. (2014). In Vitro Analysis of Riboswitch–Spinach Aptamer Fusions as Metabolite-Sensing Fluorescent Biosensors. Methods in enzymology on CD-ROM/Methods in enzymology. 550. 147–172. 25 indexed citations
17.
Leppek, Kathrin, Johanna Schott, Sonja Reitter, et al.. (2013). Roquin Promotes Constitutive mRNA Decay via a Conserved Class of Stem-Loop Recognition Motifs. Cell. 153(4). 869–881. 249 indexed citations
18.
Hammond, Ming C., et al.. (2009). What does our past involvement with computers tell us? A view from the research community.. Rejuvenation Research. 13(2-3). 210–3. 2 indexed citations
19.
Hammond, Ming C., Andreas Wachter, & Ronald R. Breaker. (2009). A plant 5S ribosomal RNA mimic regulates alternative splicing of transcription factor IIIA pre-mRNAs. Nature Structural & Molecular Biology. 16(5). 541–549. 44 indexed citations
20.
Sudarsan, Narasimhan, Ming C. Hammond, Kirsten F. Block, et al.. (2006). Tandem Riboswitch Architectures Exhibit Complex Gene Control Functions. Science. 314(5797). 300–304. 201 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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