Dan T. Gillespie
- Molecular Biology
- Genetics
- Statistical and Nonlinear Physics top 10%
- Biomedical Engineering
- Modeling and Simulation top 10%
- Co-authors
- Linda PetzoldYang CaoMin K. RohMustafa KhammashBernie J. DaigleKevin R. SanftMartin Ferguson-PellCrystal L. MacLellan
- Topics
- Gene Regulatory Network Analysis (10 papers)Advanced Thermodynamics and Statistical Mechanics (3 papers)DNA and Biological Computing (2 papers)
- Journals
- The Journal of Chemical PhysicsJournal of Computational PhysicsInternational Journal of Robust and Nonlinear Control
- Partner nations
- United StatesCanada
In The Last Decade
Dan T. Gillespie
12 papers receiving 427 citations
Peers
Comparison fields: 5 of 74
- Molecular Biology 365
- Genetics 99
- Statistical and Nonlinear Physics 84
- Biomedical Engineering 49
- Modeling and Simulation 34
Countries citing papers authored by Dan T. Gillespie
This map shows the geographic impact of Dan T. Gillespie'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 Dan T. Gillespie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan T. Gillespie more than expected).
Fields of papers citing papers by Dan T. Gillespie
This network shows the impact of papers produced by Dan T. Gillespie. 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 Dan T. Gillespie. The network helps show where Dan T. Gillespie may publish in the future.
Co-authorship network of co-authors of Dan T. Gillespie
This figure shows the co-authorship network connecting the top 25 collaborators of Dan T. Gillespie. A scholar is included among the top collaborators of Dan T. Gillespie 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 Dan T. Gillespie. Dan T. Gillespie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 19 | |
| 3 | 28 | |
| 4 | 14 | |
| 5 | 7 | |
| 6 | 28 | |
| 7 | 50 | |
| 8 | 23 | |
| 9 | 14 | |
| 10 | 79 | |
| 11 | Stochastic Modeling of Gene Regulatory Networks y | 22 |
| 12 | 142 |
About Dan T. Gillespie
Dan T. Gillespie is a scholar working on Biophysics, Statistical and Nonlinear Physics and Modeling and Simulation, having authored 12 papers that have together received 433 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (10 papers), Advanced Thermodynamics and Statistical Mechanics (3 papers) and DNA and Biological Computing (2 papers). The work is most often cited by research in Modeling and Simulation (34 citations), Statistical and Nonlinear Physics (84 citations) and Molecular Biology (365 citations). Dan T. Gillespie has collaborated with scholars based in United States and Canada. Frequent co-authors include Linda Petzold, Yang Cao, Min K. Roh, Mustafa Khammash, Bernie J. Daigle, Kevin R. Sanft, Martin Ferguson-Pell, Crystal L. MacLellan and Patricia J. Manns. Their work appears in journals such as The Journal of Chemical Physics, Journal of Computational Physics and International Journal of Robust and Nonlinear Control.
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.