David M. Booth

1.4k total citations
31 papers, 981 citations indexed

About

David M. Booth is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, David M. Booth has authored 31 papers receiving a total of 981 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Computer Vision and Pattern Recognition and 9 papers in Aerospace Engineering. Recurrent topics in David M. Booth's work include Mitochondrial Function and Pathology (7 papers), Pancreatitis Pathology and Treatment (5 papers) and Remote-Sensing Image Classification (5 papers). David M. Booth is often cited by papers focused on Mitochondrial Function and Pathology (7 papers), Pancreatitis Pathology and Treatment (5 papers) and Remote-Sensing Image Classification (5 papers). David M. Booth collaborates with scholars based in United Kingdom, United States and Australia. David M. Booth's co-authors include György Hajnóczky, Péter Várnai, Rajarshi Mukherjee, Balázs Enyedi, Miklós Geiszt, Robert Sutton, David N. Criddle, Suresh K. Joseph, Ole H. Petersen and Alexei V. Tepikin and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Molecular Cell.

In The Last Decade

David M. Booth

29 papers receiving 966 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David M. Booth United Kingdom 14 454 403 187 163 158 31 981
Xiao-Qing Dai Canada 21 795 1.8× 782 1.9× 126 0.7× 121 0.7× 149 0.9× 42 1.5k
Eijiro Yamada Japan 20 601 1.3× 318 0.8× 235 1.3× 141 0.9× 196 1.2× 100 1.2k
Zhiming Ge China 16 317 0.7× 212 0.5× 122 0.7× 69 0.4× 233 1.5× 38 775
Robert W. Schwenk Netherlands 24 918 2.0× 349 0.9× 239 1.3× 98 0.6× 145 0.9× 32 1.6k
Guanlan Xu United States 17 669 1.5× 603 1.5× 120 0.6× 42 0.3× 227 1.4× 27 1.3k
Huaitao Yang United States 15 391 0.9× 196 0.5× 240 1.3× 58 0.4× 38 0.2× 26 898
Tom J.J. Schirris Netherlands 17 458 1.0× 217 0.5× 68 0.4× 93 0.6× 72 0.5× 35 845
Ana Marta Pereira Portugal 13 579 1.3× 259 0.6× 123 0.7× 53 0.3× 296 1.9× 33 1.4k
Xian-Cheng Jiang United States 17 840 1.9× 497 1.2× 228 1.2× 113 0.7× 149 0.9× 22 1.6k
Shigeru Yatoh Japan 25 793 1.7× 705 1.7× 344 1.8× 86 0.5× 116 0.7× 44 1.7k

Countries citing papers authored by David M. Booth

Since Specialization
Citations

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

Fields of papers citing papers by David M. Booth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Booth

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Booth. A scholar is included among the top collaborators of David M. Booth 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 David M. Booth. David M. Booth 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.
Booth, David M., Péter Várnai, Suresh K. Joseph, & György Hajnóczky. (2022). Fluorescence imaging detection of nanodomain redox signaling events at organellar contacts. STAR Protocols. 3(1). 101119–101119. 5 indexed citations
2.
Çoku, Jorida, David M. Booth, J. Škoda, et al.. (2022). Reduced ER–mitochondria connectivity promotes neuroblastoma multidrug resistance. The EMBO Journal. 41(8). e108272–e108272. 23 indexed citations
3.
Booth, David M., Péter Várnai, Suresh K. Joseph, & György Hajnóczky. (2021). Oxidative bursts of single mitochondria mediate retrograde signaling toward the ER. Molecular Cell. 81(18). 3866–3876.e2. 48 indexed citations
4.
Young, Michael, Zachary T. Schug, David M. Booth, et al.. (2021). Metabolic adaptation to the chronic loss of Ca2+ signaling induced by KO of IP3 receptors or the mitochondrial Ca2+ uniporter. Journal of Biological Chemistry. 298(1). 101436–101436. 16 indexed citations
5.
Joseph, Suresh K., David M. Booth, Michael Young, & György Hajnóczky. (2019). Redox regulation of ER and mitochondrial Ca2+ signaling in cell survival and death. Cell Calcium. 79. 89–97. 40 indexed citations
6.
Joseph, Suresh K., Michael Young, Kamil J. Alzayady, et al.. (2018). Redox regulation of type-I inositol trisphosphate receptors in intact mammalian cells. Journal of Biological Chemistry. 293(45). 17464–17476. 45 indexed citations
7.
Booth, David M., Balázs Enyedi, Miklós Geiszt, Péter Várnai, & György Hajnóczky. (2016). Redox Nanodomains Are Induced by and Control Calcium Signaling at the ER-Mitochondrial Interface. Molecular Cell. 63(2). 240–248. 246 indexed citations
8.
Booth, David M., Suresh K. Joseph, & György Hajnóczky. (2016). Subcellular ROS imaging methods: Relevance for the study of calcium signaling. Cell Calcium. 60(2). 65–73. 19 indexed citations
9.
Huang, Wei, Matthew C. Cane, Rajarshi Mukherjee, et al.. (2015). Caffeine protects against experimental acute pancreatitis by inhibition of inositol 1,4,5-trisphosphate receptor-mediated Ca 2+ release. Gut. 66(2). 301–313. 77 indexed citations
10.
Booth, David M., et al.. (2014). Fusion of Multiple Sensor Data to Recognise Moving Objects in Wide Area Motion Imagery. 20. 1–8. 3 indexed citations
11.
Booth, David M., et al.. (2013). Application of Detection and Recognition Algorithms to Persistent Wide Area Surveillance. 2781. 1–8. 4 indexed citations
12.
Huang, Wei, Diane Latawiec, Kun Jiang, et al.. (2012). Review of experimental animal models of biliary acute pancreatitis and recent advances in basic research. HPB. 14(2). 73–81. 42 indexed citations
13.
Booth, David M., John A. Murphy, Rajarshi Mukherjee, et al.. (2011). Reactive Oxygen Species Induced by Bile Acid Induce Apoptosis and Protect Against Necrosis in Pancreatic Acinar Cells. Gastroenterology. 140(7). 2116–2125. 153 indexed citations
14.
Booth, David M., Rajarshi Mukherjee, Robert Sutton, & David N. Criddle. (2011). Calcium and Reactive Oxygen Species in Acute Pancreatitis: Friend or Foe?. Antioxidants and Redox Signaling. 15(10). 2683–2698. 59 indexed citations
15.
Criddle, David N., David M. Booth, Rajarshi Mukherjee, et al.. (2009). Cholecystokinin-58 and cholecystokinin-8 exhibit similar actions on calcium signaling, zymogen secretion, and cell fate in murine pancreatic acinar cells. American Journal of Physiology-Gastrointestinal and Liver Physiology. 297(6). G1085–G1092. 22 indexed citations
16.
Booth, David M., et al.. (2005). Federated Exploitation of All-Source Imagery. 36–36. 1 indexed citations
17.
Booth, David M., et al.. (2003). Using models to recognise man-made objects. 56. 33–40. 6 indexed citations
18.
Harvey, P., et al.. (2003). Software tools for assisting the multisource imagery analyst. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5203. 163–163. 3 indexed citations
19.
Booth, David M., et al.. (1999). Using Models to Detect Man-Made Objects. 33. 2 indexed citations
20.
Booth, David M., et al.. (1992). Combining the Opinions of Several Early Vision Modules using a Multi-Layer Perceptron.. 6 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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