Brian Ingalls

2.1k total citations
79 papers, 1.4k citations indexed

About

Brian Ingalls is a scholar working on Molecular Biology, Control and Systems Engineering and Genetics. According to data from OpenAlex, Brian Ingalls has authored 79 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 13 papers in Control and Systems Engineering and 13 papers in Genetics. Recurrent topics in Brian Ingalls's work include Gene Regulatory Network Analysis (32 papers), Microbial Metabolic Engineering and Bioproduction (17 papers) and Viral Infectious Diseases and Gene Expression in Insects (15 papers). Brian Ingalls is often cited by papers focused on Gene Regulatory Network Analysis (32 papers), Microbial Metabolic Engineering and Bioproduction (17 papers) and Viral Infectious Diseases and Gene Expression in Insects (15 papers). Brian Ingalls collaborates with scholars based in Canada, United States and Germany. Brian Ingalls's co-authors include Herbert M. Sauro, Eduardo D. Sontag, Matthew P. Scott, Mads Kærn, C. Barnes, Terence Hwa, Alex J. H. Fedorec, David R. McMillen, Jordan Ang and Brendan J. McConkey and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Environmental Science & Technology and Applied and Environmental Microbiology.

In The Last Decade

Brian Ingalls

73 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian Ingalls Canada 22 838 313 176 100 85 79 1.4k
Alejandro F. Villaverde Spain 24 929 1.1× 328 1.0× 124 0.7× 129 1.3× 123 1.4× 61 1.8k
Steffen Waldherr Germany 18 584 0.7× 193 0.6× 77 0.4× 87 0.9× 34 0.4× 85 900
Diego A. Oyarzún United Kingdom 20 1.2k 1.5× 147 0.5× 284 1.6× 217 2.2× 33 0.4× 66 1.7k
Jean‐Luc Gouzé France 22 1.1k 1.3× 1.1k 3.6× 360 2.0× 80 0.8× 199 2.3× 125 2.5k
Ioannis Lestas United Kingdom 15 355 0.4× 455 1.5× 93 0.5× 52 0.5× 76 0.9× 74 1.1k
Tim Maiwald Germany 12 954 1.1× 151 0.5× 140 0.8× 71 0.7× 51 0.6× 14 1.9k
Carmen G. Moles Spain 7 524 0.6× 238 0.8× 76 0.4× 55 0.6× 24 0.3× 10 1.0k
Andreas Kremling Germany 25 1.4k 1.6× 121 0.4× 374 2.1× 266 2.7× 26 0.3× 77 1.8k
Grégory Batt France 18 891 1.1× 41 0.1× 188 1.1× 162 1.6× 22 0.3× 38 1.2k
Yalu Li China 16 378 0.5× 168 0.5× 71 0.4× 52 0.5× 44 0.5× 52 751

Countries citing papers authored by Brian Ingalls

Since Specialization
Citations

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

Fields of papers citing papers by Brian Ingalls

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Ingalls

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Ingalls. A scholar is included among the top collaborators of Brian Ingalls 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 Brian Ingalls. Brian Ingalls 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.
Stavropoulos, Andreas, Stephen Graves, Guowei Che, et al.. (2025). Comparative proteomics of biofilm development in Pseudoalteromonas tunicata discovers a distinct family of Ca 2+ -dependent adhesins. mBio. 16(6). e0106925–e0106925. 1 indexed citations
2.
Weldon, M. K., et al.. (2025). Harnessing synthetic biology to empower a circular plastics economy. Canadian Journal of Microbiology. 71. 1–20.
3.
4.
Mérindol, Natacha, et al.. (2024). No two clones are alike: characterization of heterologous subpopulations in a transgenic cell line of the model diatom Phaeodactylum tricornutum. Microbial Cell Factories. 23(1). 286–286. 1 indexed citations
5.
Aucoin, Marc G., et al.. (2024). Degradation of polyethylene terephthalate (PET) plastics by wastewater bacteria engineered via conjugation. Microbial Biotechnology. 17(9). e70015–e70015. 7 indexed citations
6.
Joseph, Jamie W., et al.. (2023). Kinetic modelling of β ‐cell metabolism reveals control points in the insulin‐regulating pyruvate cycling pathways. IET Systems Biology. 17(6). 303–315. 2 indexed citations
7.
8.
Ingalls, Brian, et al.. (2022). NLoed: A Python Package for Nonlinear Optimal Experimental Design in Systems Biology. ACS Synthetic Biology. 11(12). 3921–3928. 5 indexed citations
9.
Ingalls, Brian, et al.. (2022). Deep reinforcement learning for optimal experimental design in biology. PLoS Computational Biology. 18(11). e1010695–e1010695. 15 indexed citations
10.
Aucoin, Marc G., et al.. (2022). Calibrating spatiotemporal models of microbial communities to microscopy data: A review. PLoS Computational Biology. 18(10). e1010533–e1010533. 4 indexed citations
11.
Diep, Patrick, Xingyu Chen, Radhakrishnan Mahadevan, et al.. (2021). Advancing undergraduate synthetic biology education: insights from a Canadian iGEM student perspective. Canadian Journal of Microbiology. 67(10). 749–770. 8 indexed citations
12.
Ingalls, Brian, et al.. (2020). Gene-Centric Model Approaches for Accurate Prediction of Pesticide Biodegradation in Soils. Environmental Science & Technology. 54(21). 13638–13650. 16 indexed citations
13.
Fedorec, Alex J. H., et al.. (2020). Deep reinforcement learning for the control of microbial co-cultures in bioreactors. PLoS Computational Biology. 16(4). e1007783–e1007783. 82 indexed citations
14.
Venkiteswaran, Jason J., Sherry L. Schiff, & Brian Ingalls. (2019). Quantifying the fate of wastewater nitrogen discharged to a Canadian river. FACETS. 4(1). 315–335. 8 indexed citations
15.
Hamadeh, Abdullah, Brian Ingalls, & Eduardo D. Sontag. (2013). Transient dynamic phenotypes as criteria for model discrimination: fold-change detection in Rhodobacter sphaeroides chemotaxis. Journal of The Royal Society Interface. 10(80). 20120935–20120935. 12 indexed citations
16.
Wei, Catherine, et al.. (2011). Development of a mathematical model for evaluating the dynamics of normal and apoptotic Chinese hamster ovary cells. Biotechnology Progress. 27(5). 1197–1205. 37 indexed citations
17.
Ang, Jordan, Sangram Bagh, Brian Ingalls, & David R. McMillen. (2010). Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network. Journal of Theoretical Biology. 266(4). 723–738. 67 indexed citations
18.
Abedi, Vida, et al.. (2010). Estimating the Stochastic Bifurcation Structure of Cellular Networks. PLoS Computational Biology. 6(3). e1000699–e1000699. 27 indexed citations
19.
Ingalls, Brian. (2004). Autonomously oscillating biochemical systems: parametric sensitivity of extrema and period. PubMed. 1(1). 62–70. 28 indexed citations
20.
Ingalls, Brian & Herbert M. Sauro. (2003). Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories. Journal of Theoretical Biology. 222(1). 23–36. 111 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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Breakdown of academic impact, for papers by Alejandro F. Villaverde Breakdown of academic impact, for papers by Steffen Waldherr Breakdown of academic impact, for papers by Diego A. Oyarzún Breakdown of academic impact, for papers by Jean‐Luc Gouzé Breakdown of academic impact, for papers by Ioannis Lestas Breakdown of academic impact, for papers by Tim Maiwald Breakdown of academic impact, for papers by Carmen G. Moles Breakdown of academic impact, for papers by Andreas Kremling Breakdown of academic impact, for papers by Grégory Batt Breakdown of academic impact, for papers by Yalu Li
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