Mark A. Chambers

4.8k total citations
144 papers, 3.5k citations indexed

About

Mark A. Chambers is a scholar working on Infectious Diseases, Epidemiology and Immunology. According to data from OpenAlex, Mark A. Chambers has authored 144 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Infectious Diseases, 66 papers in Epidemiology and 47 papers in Immunology. Recurrent topics in Mark A. Chambers's work include Tuberculosis Research and Epidemiology (79 papers), Mycobacterium research and diagnosis (58 papers) and Immune responses and vaccinations (31 papers). Mark A. Chambers is often cited by papers focused on Tuberculosis Research and Epidemiology (79 papers), Mycobacterium research and diagnosis (58 papers) and Immune responses and vaccinations (31 papers). Mark A. Chambers collaborates with scholars based in United Kingdom, United States and Ireland. Mark A. Chambers's co-authors include R. Glyn Hewinson, Adam O. Whelan, Richard J. Delahay, H. Martin Vordermeier, Bryce M. Buddle, Sandrine Lesellier, Dolores Gavier‐Widén, Paul Cockle, Konstantin P. Lyashchenko and Deanna Dalley and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and Analytical Chemistry.

In The Last Decade

Mark A. Chambers

136 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark A. Chambers United Kingdom 36 2.3k 1.8k 963 620 454 144 3.5k
Eamonn Gormley Ireland 36 2.3k 1.0× 1.9k 1.1× 660 0.7× 635 1.0× 568 1.3× 116 3.5k
Phalguni Gupta United States 38 2.5k 1.1× 1.1k 0.6× 1.6k 1.6× 903 1.5× 423 0.9× 165 5.5k
Anders Fomsgaard Denmark 38 1.5k 0.6× 1.4k 0.8× 1.4k 1.5× 1.3k 2.1× 273 0.6× 190 4.8k
W. Ray Waters United States 45 4.1k 1.8× 4.0k 2.3× 1.3k 1.4× 1.1k 1.8× 1.4k 3.1× 205 6.5k
Xianzhu Xia China 32 2.0k 0.9× 2.0k 1.1× 671 0.7× 868 1.4× 186 0.4× 233 4.4k
Mitchell V. Palmer United States 49 4.4k 1.9× 4.3k 2.4× 1.3k 1.4× 1.0k 1.6× 1.3k 3.0× 242 7.3k
Emanuele Montomoli Italy 38 2.1k 0.9× 2.8k 1.6× 1.3k 1.3× 940 1.5× 191 0.4× 210 5.1k
Francisco J. Salguero United Kingdom 37 2.0k 0.9× 863 0.5× 730 0.8× 890 1.4× 204 0.4× 188 4.4k
Ursula J. Buchholz United States 39 3.3k 1.4× 4.1k 2.3× 866 0.9× 500 0.8× 125 0.3× 96 5.6k
Gregers Jungersen Denmark 28 654 0.3× 918 0.5× 622 0.6× 502 0.8× 428 0.9× 96 2.7k

Countries citing papers authored by Mark A. Chambers

Since Specialization
Citations

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

Fields of papers citing papers by Mark A. Chambers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark A. Chambers. 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 Mark A. Chambers. The network helps show where Mark A. Chambers may publish in the future.

Co-authorship network of co-authors of Mark A. Chambers

This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Chambers. A scholar is included among the top collaborators of Mark A. Chambers 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 Mark A. Chambers. Mark A. Chambers 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.
Felipe-Sotelo, M., Neil Ward, Mark A. Chambers, et al.. (2025). Impact of manure and artificial fertilizer application on metal and metalloid distributions in agricultural soils and crops. Chemosphere. 375. 144243–144243. 1 indexed citations
2.
Robertson, Andrew, Mark A. Chambers, Graham Smith, et al.. (2025). Can badger vaccination contribute to bovine TB control? A narrative review of the evidence. Preventive Veterinary Medicine. 238. 106464–106464.
3.
Krause, Robert, Paul Ogongo, Liku B. Tezera, et al.. (2024). B cell heterogeneity in human tuberculosis highlights compartment-specific phenotype and functional roles. Communications Biology. 7(1). 584–584. 9 indexed citations
4.
Costa, Catia, et al.. (2023). Noninvasive drug adherence monitoring of antipsychotic patients via finger sweat testing. Frontiers in Chemistry. 11. 1245089–1245089. 6 indexed citations
5.
Macdonald, Alastair, Mark A. Chambers, Roberto M. La Ragione, et al.. (2020). Addressing Infection Risk in Veterinary Practice through the Innovative Application of Interactive 3D Animation Methods. The Design Journal. 24(1). 51–72. 1 indexed citations
6.
Lee, David, et al.. (2018). Isolation and characterisation of alveolar type II pneumocytes from adult bovine lung. Scientific Reports. 8(1). 11927–11927. 20 indexed citations
7.
Carter, Stephen P., Andrew Robertson, Kate L. Palphramand, et al.. (2018). Bait uptake by wild badgers and its implications for oral vaccination against tuberculosis. PLoS ONE. 13(11). e0206136–e0206136. 10 indexed citations
8.
Palphramand, Kate L., Richard J. Delahay, Andrew Robertson, et al.. (2017). Field evaluation of candidate baits for oral delivery of BCG vaccine to European badgers, Meles meles. Vaccine. 35(34). 4402–4407. 12 indexed citations
9.
Chambers, Mark A., et al.. (2016). Diagnosis of tuberculosis in groups of badgers: an exploration of the impact of trapping efficiency, infection prevalence and the use of multiple tests. Epidemiology and Infection. 144(8). 1717–1727. 18 indexed citations
10.
Robertson, Andrew, et al.. (2016). Behaviour of European badgers and non-target species towards candidate baits for oral delivery of a tuberculosis vaccine. Preventive Veterinary Medicine. 135. 95–101. 13 indexed citations
11.
Corner, L.A., Eamon Costello, Sandrine Lesellier, et al.. (2010). Oral vaccination of badgers (Meles meles) with BCG and protective immunity against endobronchial challenge with Mycobacterium bovis. Vaccine. 28(38). 6265–6272. 64 indexed citations
12.
Bessant, Conrad, et al.. (2009). Evaluation of a combination of SIFT-MS and multivariate data analysis for the diagnosis of Mycobacterium bovis in wild badgers. The Analyst. 134(9). 1922–1922. 22 indexed citations
13.
Gavier‐Widén, Dolores, et al.. (2009). A review of infection of wildlife hosts withMycobacterium bovisand the diagnostic difficulties of the ‘no visible lesion’ presentation. New Zealand Veterinary Journal. 57(3). 122–131. 46 indexed citations
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Hamasur, Beston, Dolores Gavier‐Widén, Mark A. Chambers, et al.. (2005). Nasal boost with adjuvanted heat-killed BCG or arabinomannan–protein conjugate improves primary BCG-induced protection in C57BL/6 mice. Tuberculosis. 85(1-2). 107–114. 32 indexed citations
17.
Chambers, Mark A.. (2000). Queuing network construction using artificial neural networks /. OhioLink ETD Center (Ohio Library and Information Network). 2 indexed citations
18.
Chambers, Mark A., et al.. (2000). Biochemical and haematological parameters associated with tuberculosis in European badgers. Veterinary Record. 146(25). 734–735. 1 indexed citations
19.
Lulla, Kamlesh, Markus Helfert, D. E. Pitts, et al.. (1993). Earth observations during space shuttle flight sts 50: Columbia's mission to planet earth, June 25‐July 9,1992. Geocarto International. 8(2). 67–80.
20.
Field, E. J. & Mark A. Chambers. (1970). Rickettsial Antibodies in Multiple Sclerosis. BMJ. 1(5687). 30–32. 3 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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