James G. Booth

4.7k total citations · 1 hit paper
87 papers, 3.1k citations indexed

About

James G. Booth is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, James G. Booth has authored 87 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Statistics and Probability, 18 papers in Artificial Intelligence and 15 papers in Molecular Biology. Recurrent topics in James G. Booth's work include Statistical Methods and Inference (23 papers), Statistical Methods and Bayesian Inference (20 papers) and Bayesian Methods and Mixture Models (16 papers). James G. Booth is often cited by papers focused on Statistical Methods and Inference (23 papers), Statistical Methods and Bayesian Inference (20 papers) and Bayesian Methods and Mixture Models (16 papers). James G. Booth collaborates with scholars based in United States, Australia and Germany. James G. Booth's co-authors include James P. Hobert, Ronald W. Butler, Matthew Connolly, Bruce V. Lewenstein, Paul M. Davis, Daniel H. Simon, George Casella, John E. Kolassa, Peter Hall and Brian Caffo and has published in prestigious journals such as Nature Communications, Neuron and Nature Genetics.

In The Last Decade

James G. Booth

81 papers receiving 3.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia

2010 578 citations María E. Figueroa, Sanne Lugthart et al. Cancer Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James G. Booth United States	25	956	918	491	390	313	87	3.1k
Somnath Datta United States	48	1.6k 1.7×	1.3k 1.5×	810 1.6×	158 0.4×	113 0.4×	208	8.1k
Philip J. Brown United Kingdom	39	829 0.9×	1.4k 1.5×	700 1.4×	53 0.1×	260 0.8×	134	5.1k
M. J. R. Healy United Kingdom	27	655 0.7×	807 0.9×	289 0.6×	91 0.2×	245 0.8×	97	5.2k
Nitin R. Patel United States	27	284 0.3×	788 0.9×	382 0.8×	105 0.3×	121 0.4×	64	4.0k
Jerry Nedelman United States	24	450 0.5×	587 0.6×	260 0.5×	85 0.2×	180 0.6×	67	2.5k
F Yates United States	26	706 0.7×	606 0.7×	217 0.4×	99 0.3×	168 0.5×	102	3.0k
Tomasz Burzykowski Belgium	42	989 1.0×	1.6k 1.8×	156 0.3×	153 0.4×	260 0.8×	195	6.6k
Michael A. Martin Australia	29	582 0.6×	963 1.0×	317 0.6×	29 0.1×	146 0.5×	101	3.9k
M. L. Tiku Canada	36	408 0.4×	1.9k 2.0×	283 0.6×	73 0.2×	562 1.8×	142	4.2k
T. M. F. Smith United Kingdom	25	709 0.7×	917 1.0×	231 0.5×	73 0.2×	56 0.2×	96	3.6k

Countries citing papers authored by James G. Booth

Since Specialization

Citations

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

Fields of papers citing papers by James G. Booth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James G. Booth

This figure shows the co-authorship network connecting the top 25 collaborators of James G. Booth. A scholar is included among the top collaborators of James G. 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 James G. Booth. James G. Booth 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

Zhang, Yingying, Alden King-Yung Leung, Le Li, et al.. (2025). A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology. Nature Communications. 16(1). 975–975. 2 indexed citations

Hirschl, Thomas A., James G. Booth, & Leland Glenna. (2023). Religion and Climate Change Indifference: Linking the Sacred to the Social. Review of European Studies. 15(1). 11–11. 1 indexed citations

Carstensen, Michelle, Daniel P. Walsh, Daniel J. Storm, et al.. (2022). Informing Surveillance through the Characterization of Outbreak Potential of Chronic Wasting Disease in White-Tailed Deer. Ecological Modelling. 471. 110054–110054. 4 indexed citations

Tippens, Nathaniel D., Jin Liang, Alden King-Yung Leung, et al.. (2020). Transcription imparts architecture, function and logic to enhancer units. Nature Genetics. 52(10). 1067–1075. 49 indexed citations

Bar, Haim, James G. Booth, & Martin T. Wells. (2019). A Scalable Empirical Bayes Approach to Variable Selection in Generalized Linear Models. Journal of Computational and Graphical Statistics. 29(3). 535–546. 4 indexed citations

Cazer, Casey L., Mohammad A. Al‐Mamun, William J. Love, et al.. (2019). Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining. Frontiers in Microbiology. 10. 1359–1359. 15 indexed citations

Lanzas, Cristina, et al.. (2019). Estimation of multidrug resistance variability in the National Antimicrobial Monitoring System. Preventive Veterinary Medicine. 167. 137–145. 3 indexed citations

Love, William J., et al.. (2018). Phenotypical resistance correlation networks for 10 non-typhoidalSalmonellasubpopulations in an active antimicrobial surveillance programme. Epidemiology and Infection. 146(8). 991–1002. 4 indexed citations

Love, William J., et al.. (2016). Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012. PLoS Computational Biology. 12(11). e1005160–e1005160. 18 indexed citations

10.

Bar, Haim, James G. Booth, & Martin T. Wells. (2012). A Mixture-Model Approach for Parallel Testing for Unequal Variances. Statistical Applications in Genetics and Molecular Biology. 11(1). Article 8–Article 8. 11 indexed citations

11.

Rosenbaum, Miriam A., Haim Bar, Qasim Khalil Beg, et al.. (2012). Transcriptional Analysis of Shewanella oneidensis MR-1 with an Electrode Compared to Fe(III)Citrate or Oxygen as Terminal Electron Acceptor. PLoS ONE. 7(2). e30827–e30827. 51 indexed citations

12.

Booth, James G., Kirsten Eilertson, Paul Dominic B. Olinares, & Haiyuan Yu. (2011). A Bayesian Mixture Model for Comparative Spectral Count Data in Shotgun Proteomics. Molecular & Cellular Proteomics. 10(8). M110.007203–M110.007203. 13 indexed citations

13.

Rosenbaum, Miriam A., Haim Bar, Qasim Khalil Beg, et al.. (2010). Shewanella oneidensis in a lactate-fed pure-culture and a glucose-fed co-culture with Lactococcus lactis with an electrode as electron acceptor. Bioresource Technology. 102(3). 2623–2628. 71 indexed citations

14.

Sainudiin, Raazesh, Kevin Thornton, Jennifer Harlow, et al.. (2010). Experiments with the Site Frequency Spectrum. Bulletin of Mathematical Biology. 73(4). 829–872. 6 indexed citations

15.

Figueroa, María E., Sanne Lugthart, Yushan Li, et al.. (2010). DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia. Cancer Cell. 17(1). 13–27. 578 indexed citations breakdown →

16.

Davis, Paul M., Bruce V. Lewenstein, Daniel H. Simon, James G. Booth, & Matthew Connolly. (2008). Open access publishing, article downloads, and citations: randomised controlled trial. BMJ. 337(jul31 1). a568–a568. 269 indexed citations

17.

Holloway, J. Kim, James G. Booth, Winfried Edelmann, Clare H. McGowan, & Paula E. Cohen. (2008). MUS81 Generates a Subset of MLH1-MLH3–Independent Crossovers in Mammalian Meiosis. PLoS Genetics. 4(9). e1000186–e1000186. 152 indexed citations

18.

Brooks, Marjory B., et al.. (2008). Indirect carrier detection of canine haemophilia A using factor VIII microsatellite markers. Animal Genetics. 39(3). 278–283. 2 indexed citations

19.

Booth, James G. & John E. Kolassa. (1999). Series Approximation Methods in Statistics. Journal of the American Statistical Association. 94(445). 343–343. 97 indexed citations

20.

Booth, James G., et al.. (1993). Fasciclin I and II have distinct roles in the development of grasshopper pioneer neurons. Neuron. 11(3). 409–421. 48 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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