Jonathan M. Keith

2.4k total citations
89 papers, 1.7k citations indexed

About

Jonathan M. Keith is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Jonathan M. Keith has authored 89 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 20 papers in Genetics and 13 papers in Artificial Intelligence. Recurrent topics in Jonathan M. Keith's work include Genomics and Phylogenetic Studies (17 papers), RNA and protein synthesis mechanisms (10 papers) and Bayesian Methods and Mixture Models (7 papers). Jonathan M. Keith is often cited by papers focused on Genomics and Phylogenetic Studies (17 papers), RNA and protein synthesis mechanisms (10 papers) and Bayesian Methods and Mixture Models (7 papers). Jonathan M. Keith collaborates with scholars based in Australia, United States and United Kingdom. Jonathan M. Keith's co-authors include Camille Locht, Dirk P. Kroese, Bruce Chesebro, Richard Race, H. Fraenkel‐Conrat, Bernard Moss, M J Ensinger, Georgy Sofronov, K S Marchitto and Witold Cieplak and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Jonathan M. Keith

86 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jonathan M. Keith Australia	25	820	247	182	165	144	89	1.7k
Paolo Di Tommaso Spain	12	1.1k 1.3×	204 0.8×	272 1.5×	133 0.8×	108 0.8×	25	1.6k
Alexander Rosenberg Johansen Denmark	11	1.2k 1.5×	184 0.7×	464 2.5×	103 0.6×	139 1.0×	13	2.2k
Jennifer Bryan Canada	26	1.1k 1.4×	149 0.6×	136 0.7×	376 2.3×	318 2.2×	62	2.9k
Philip Bucher Germany	9	2.0k 2.4×	273 1.1×	353 1.9×	54 0.3×	280 1.9×	12	2.8k
Christophe Blanchet France	18	1.9k 2.3×	349 1.4×	348 1.9×	88 0.5×	201 1.4×	36	2.9k
Erik Bongcam‐Rudloff Sweden	27	1.2k 1.5×	318 1.3×	274 1.5×	104 0.6×	179 1.2×	114	2.3k
James B. Munro United States	20	732 0.9×	319 1.3×	121 0.7×	43 0.3×	95 0.7×	33	1.8k
Fiona McCarthy United States	25	968 1.2×	420 1.7×	307 1.7×	47 0.3×	187 1.3×	67	2.0k
E. Michael Gertz United States	18	1.5k 1.8×	453 1.8×	421 2.3×	67 0.4×	271 1.9×	42	2.7k
Tadashi Imanishi Japan	28	1.4k 1.7×	507 2.1×	212 1.2×	68 0.4×	479 3.3×	116	2.5k

Countries citing papers authored by Jonathan M. Keith

Since Specialization

Citations

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

Fields of papers citing papers by Jonathan M. Keith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan M. Keith

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan M. Keith. A scholar is included among the top collaborators of Jonathan M. Keith 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 Jonathan M. Keith. Jonathan M. Keith 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

Flegg, Jennifer A., et al.. (2020). A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models. Royal Society Open Science. 7(3). 191315–191315. 11 indexed citations

Yen, Jian D. L., James R. Thomson, Jonathan M. Keith, et al.. (2018). Linking species richness and size diversity in birds and fishes. Ecography. 41(12). 1979–1991. 4 indexed citations

Boyd, Sarah, et al.. (2018). Bayesian change-point modeling with segmented ARMA model. PLoS ONE. 13(12). e0208927–e0208927. 7 indexed citations

Chen, Carla, Jonathan M. Keith, & Kerrie Mengersen. (2017). Accurate phenotyping: Reconciling approaches through Bayesian model averaging. PLoS ONE. 12(4). e0176136–e0176136. 1 indexed citations

Keith, Jonathan M., et al.. (2016). Sequence Segmentation with changeptGUI. Methods in molecular biology. 1525. 293–312. 2 indexed citations

Woolfit, Megan, et al.. (2015). Discovery of Putative Small Non-Coding RNAs from the Obligate Intracellular Bacterium Wolbachia pipientis. PLoS ONE. 10(3). e0118595–e0118595. 10 indexed citations

Azad, AKM, Alfons Lawen, & Jonathan M. Keith. (2015). Prediction of signaling cross-talks contributing to acquired drug resistance in breast cancer cells by Bayesian statistical modeling. BMC Systems Biology. 9(1). 2–2. 18 indexed citations

Keith, Jonathan M. & Daniel Spring. (2013). Agent-based Bayesian approach to monitoring the progress of invasive species eradication programs. Proceedings of the National Academy of Sciences. 110(33). 13428–13433. 27 indexed citations

Chen, Carla, et al.. (2011). Methods for Identifying SNP Interactions: A Review on Variations of Logic Regression, Random Forest and Bayesian Logistic Regression. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(6). 1580–1591. 71 indexed citations

10.

Oldmeadow, Christopher, Kerrie Mengersen, John S. Mattick, & Jonathan M. Keith. (2009). Multiple Evolutionary Rate Classes in Animal Genome Evolution. Molecular Biology and Evolution. 27(4). 942–953. 14 indexed citations

11.

Chen, Carla, Jonathan M. Keith, Dale R. Nyholt, Nicholas G. Martin, & Kerrie Mengersen. (2009). Bayesian latent trait modeling of migraine symptom data. Human Genetics. 126(2). 277–288. 12 indexed citations

12.

Keith, Jonathan M.. (2008). Bioinformatics. Methods in molecular biology. 453. v–vi. 4 indexed citations

13.

Keith, Jonathan M.. (2008). Bioinformatics. Methods in molecular biology. 452. v–vi. 5 indexed citations

14.

Keith, Jonathan M.. (2008). Bioinformatics: Volume I Data, Sequence Analysis and Evolution (Methods in Molecular Biology). Humana Press eBooks. 2 indexed citations

15.

Sofronov, Georgy, Jonathan M. Keith, & Dirk P. Kroese. (2006). An optimal sequential procedure for a buying-selling problem with independent observations. Journal of Applied Probability. 43(2). 454–462. 11 indexed citations

16.

Keith, Jonathan M., et al.. (2004). Algorithms for sequence analysis via mutagenesis. Bioinformatics. 20(15). 2401–2410. 5 indexed citations

17.

Keith, Jonathan M., et al.. (2003). Inferring an Original Sequence from Erroneous Copies: a Bayesian Approach. Queensland's institutional digital repository (The University of Queensland). 7 indexed citations

18.

Keith, Jonathan M. & Dirk P. Kroese. (2002). Rare event simulation and combinatorial optimization using cross entropy: sequence alignment by rare event simulation. Winter Simulation Conference. 320–327. 9 indexed citations

19.

Keith, Jonathan M. & Dirk P. Kroese. (2002). SABRES: Sequence Alignment By Rare Event Simulation. 5(1). 21–9. 10 indexed citations

20.

Goletz, Theresa J., Kurt R. Klimpel, Stephen H. Leppla, Jonathan M. Keith, & Jay A. Berzofsky. (1997). Delivery of Antigens to the MHC Class I Pathway Using Bacterial Toxins. Human Immunology. 54(2). 129–136. 61 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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