Pamela Burrage

2.0k total citations
59 papers, 1.2k citations indexed

About

Pamela Burrage is a scholar working on Molecular Biology, Finance and Numerical Analysis. According to data from OpenAlex, Pamela Burrage has authored 59 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 17 papers in Finance and 12 papers in Numerical Analysis. Recurrent topics in Pamela Burrage's work include Stochastic processes and financial applications (17 papers), Gene Regulatory Network Analysis (14 papers) and Numerical methods for differential equations (9 papers). Pamela Burrage is often cited by papers focused on Stochastic processes and financial applications (17 papers), Gene Regulatory Network Analysis (14 papers) and Numerical methods for differential equations (9 papers). Pamela Burrage collaborates with scholars based in Australia, United Kingdom and Italy. Pamela Burrage's co-authors include Kevin Burrage, Tianhai Tian, Constance Brinckerhoff, Margherita Carletti, Taketomo Mitsui, Brodie Lawson, Nicole Cusimano, Christopher Drovandi, Luigi Brugnano and Blanca Rodríguez and has published in prestigious journals such as The Journal of Chemical Physics, PLoS ONE and Science Advances.

In The Last Decade

Pamela Burrage

55 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pamela Burrage Australia 17 377 346 247 156 149 59 1.2k
Floyd B. Hanson United States 17 277 0.7× 66 0.2× 47 0.2× 101 0.6× 108 0.7× 83 1.0k
István Gyöngy United Kingdom 24 1.7k 4.5× 93 0.3× 226 0.9× 219 1.4× 122 0.8× 64 2.2k
Aslak Tveito Norway 26 136 0.4× 377 1.1× 217 0.9× 85 0.5× 187 1.3× 106 2.0k
Xiaoying Han China 22 154 0.4× 158 0.5× 28 0.1× 108 0.7× 167 1.1× 100 1.4k
Qian Guo China 14 162 0.4× 45 0.1× 153 0.6× 308 2.0× 90 0.6× 50 611
Juan Soler Spain 27 68 0.2× 373 1.1× 83 0.3× 763 4.9× 543 3.6× 92 2.2k
Adam Bobrowski Poland 14 70 0.2× 133 0.4× 37 0.1× 118 0.8× 62 0.4× 72 616
Marco Di Francesco Italy 20 119 0.3× 168 0.5× 38 0.2× 613 3.9× 106 0.7× 49 1.3k
Roberto Natalini Italy 27 113 0.3× 176 0.5× 276 1.1× 250 1.6× 160 1.1× 116 2.6k
Mirosław Lachowicz Poland 21 66 0.2× 274 0.8× 36 0.1× 608 3.9× 326 2.2× 91 1.3k

Countries citing papers authored by Pamela Burrage

Since Specialization
Citations

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

Fields of papers citing papers by Pamela Burrage

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pamela Burrage. 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 Pamela Burrage. The network helps show where Pamela Burrage may publish in the future.

Co-authorship network of co-authors of Pamela Burrage

This figure shows the co-authorship network connecting the top 25 collaborators of Pamela Burrage. A scholar is included among the top collaborators of Pamela Burrage 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 Pamela Burrage. Pamela Burrage 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.
Chen, Aimin, et al.. (2024). Balanced implicit Patankar–Euler methods for positive solutions of stochastic differential equations of biological regulatory systems. The Journal of Chemical Physics. 160(6). 3 indexed citations
2.
Brugnano, Luigi, Kevin Burrage, Pamela Burrage, & Felice Iavernaro. (2024). A Spectrally Accurate Step-by-Step Method for the Numerical Solution of Fractional Differential Equations. Journal of Scientific Computing. 99(2). 4 indexed citations
3.
Burrage, Pamela, et al.. (2024). Agent-based modeling for the tumor microenvironment (TME). Mathematical Biosciences & Engineering. 21(11). 7621–7647. 2 indexed citations
4.
Lawson, Brodie, Christopher Drovandi, Pamela Burrage, et al.. (2024). Perlin noise generation of physiologically realistic cardiac fibrosis. Medical Image Analysis. 98. 103240–103240. 2 indexed citations
5.
Jenner, Adrianne L. & Pamela Burrage. (2023). Modelling the flow through ion channels at the cell membrane. International Journal of Mathematical Education in Science and Technology. 55(2). 388–406.
6.
Burrage, Pamela, et al.. (2019). Mathematical Models of Cancer Cell Plasticity. Journal of Oncology. 2019. 1–14. 18 indexed citations
7.
Burrage, Pamela, et al.. (2018). Modelling optimal delivery of bFGF to chronic wounds using ODEs. Journal of Theoretical Biology. 465. 109–116. 1 indexed citations
8.
Moroney, Timothy J., et al.. (2017). How (well) are we assisting our students in becoming 21st century stem graduates. QUT ePrints (Queensland University of Technology). 208. 1 indexed citations
9.
Lawson, Brodie, Christopher Drovandi, Pamela Burrage, Blanca Rodríguez, & Kevin Burrage. (2017). Dimension Reduction for the Emulation of Cardiac Electrophysiology Models for Single Cells and Tissue. Computing in cardiology. 1 indexed citations
10.
Barrio-Solórzano, Manuel, Kevin Burrage, & Pamela Burrage. (2015). Stochastic linear multistep methods for the simulation of chemical kinetics. UVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid). 1 indexed citations
11.
Mallet, Dann, et al.. (2015). Preparing engineering graduates for the knowledge economy through blended delivery of mathematics. QUT ePrints (Queensland University of Technology). 1 indexed citations
12.
Cusimano, Nicole, Kevin Burrage, & Pamela Burrage. (2013). Fractional models for the migration of biological cells in complex spatial domains. ANZIAM Journal. 54. 250–250. 6 indexed citations
13.
Burrage, Kevin & Pamela Burrage. (2012). Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise. QUT ePrints (Queensland University of Technology). 1 indexed citations
14.
Burrage, Kevin, Pamela Burrage, André Leier, Tatiana T. Marquez‐Lago, & Dan V. Nicolau. (2011). Stochastic simulation for spatial modelling of dynamic process in a living cell. Science & Engineering Faculty. 1 indexed citations
15.
Deleyrolle, Loic P., Brian J. Morrison, J. Alejandro López, et al.. (2011). Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays. PLoS ONE. 6(1). e15844–e15844. 69 indexed citations
16.
Burrage, Kevin, Tianhai Tian, & Pamela Burrage. (2004). A multi-scaled approach for simulating chemical reaction systems. Progress in Biophysics and Molecular Biology. 85(2-3). 217–234. 80 indexed citations
17.
Burrage, Pamela & Kevin Burrage. (2003). A variable stepsize implementation for stochastic differential equations. QUT ePrints (Queensland University of Technology).
18.
Burrage, Kevin, Pamela Burrage, & Luigi Brugnano. (2000). Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations. Science & Engineering Faculty. 2 indexed citations
19.
Burrage, Kevin & Pamela Burrage. (2000). Order conditions of stochastic Runge-Kutta methods by B-series. Queensland's institutional digital repository (The University of Queensland). 11 indexed citations
20.
Brugnano, Luigi, Kevin Burrage, & Pamela Burrage. (2000). Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations. BIT Numerical Mathematics. 40(3). 451–470. 35 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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