Robert A. McDougal

1.6k total citations
40 papers, 702 citations indexed

About

Robert A. McDougal is a scholar working on Cognitive Neuroscience, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Robert A. McDougal has authored 40 papers receiving a total of 702 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 20 papers in Molecular Biology and 11 papers in Cellular and Molecular Neuroscience. Recurrent topics in Robert A. McDougal's work include Neural dynamics and brain function (19 papers), Gene Regulatory Network Analysis (12 papers) and Cell Image Analysis Techniques (9 papers). Robert A. McDougal is often cited by papers focused on Neural dynamics and brain function (19 papers), Gene Regulatory Network Analysis (12 papers) and Cell Image Analysis Techniques (9 papers). Robert A. McDougal collaborates with scholars based in United States, China and Canada. Robert A. McDougal's co-authors include Michael L. Hines, William W. Lytton, Gordon M. Shepherd, Thomas M. Morse, Samuel A. Neymotin, Luis Marenco, Michele Migliore, Anna Bulanova, Rixin Wang and Ted Carnevale and has published in prestigious journals such as Nature, Neurology and Neuroscience.

In The Last Decade

Robert A. McDougal

37 papers receiving 694 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert A. McDougal United States 14 367 276 161 107 79 40 702
Samuel A. Neymotin United States 23 1.0k 2.9× 708 2.6× 118 0.7× 227 2.1× 45 0.6× 60 1.3k
Marja‐Leena Linne Finland 16 283 0.8× 361 1.3× 297 1.8× 55 0.5× 55 0.7× 63 789
Michael Reimann Switzerland 11 510 1.4× 297 1.1× 78 0.5× 95 0.9× 50 0.6× 45 762
Christophe Pouzat France 15 676 1.8× 776 2.8× 286 1.8× 105 1.0× 35 0.4× 33 1.2k
Timothy A. Zolnik Germany 11 348 0.9× 325 1.2× 144 0.9× 113 1.1× 53 0.7× 12 641
Sacha J. van Albada Germany 17 871 2.4× 395 1.4× 43 0.3× 238 2.2× 36 0.5× 46 1.2k
Robert C. Cannon United Kingdom 17 580 1.6× 408 1.5× 413 2.6× 142 1.3× 293 3.7× 39 1.1k
Jean‐Marie C. Bouteiller United States 11 142 0.4× 226 0.8× 158 1.0× 52 0.5× 19 0.2× 54 441
Chaoyi Li China 17 456 1.2× 117 0.4× 87 0.5× 52 0.5× 12 0.2× 55 882
Jonathan Kadmon United States 6 351 1.0× 334 1.2× 125 0.8× 48 0.4× 41 0.5× 10 689

Countries citing papers authored by Robert A. McDougal

Since Specialization
Citations

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

Fields of papers citing papers by Robert A. McDougal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert A. McDougal. 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 Robert A. McDougal. The network helps show where Robert A. McDougal may publish in the future.

Co-authorship network of co-authors of Robert A. McDougal

This figure shows the co-authorship network connecting the top 25 collaborators of Robert A. McDougal. A scholar is included among the top collaborators of Robert A. McDougal 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 Robert A. McDougal. Robert A. McDougal 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.
Choi, Eunhee, et al.. (2025). Neurological history both twinned and queried by generative artificial intelligence. Frontiers in Medicine. 11. 1496866–1496866. 1 indexed citations
2.
McDougal, Robert A., et al.. (2024). Automating literature screening and curation with applications to computational neuroscience. Journal of the American Medical Informatics Association. 31(7). 1463–1470. 1 indexed citations
3.
Choi, Eunhee, et al.. (2024). GPT-4 Performance for Neurologic Localization. Neurology Clinical Practice. 14(3). e200293–e200293. 5 indexed citations
4.
Mullin, Sarah, Robert A. McDougal, Kei‐Hoi Cheung, et al.. (2024). Chemical entity normalization for successful translational development of Alzheimer’s disease and dementia therapeutics. Journal of Biomedical Semantics. 15(1). 13–13. 1 indexed citations
5.
Chartash, David, et al.. (2023). A pipeline for the retrieval and extraction of domain-specific information with application to COVID-19 immune signatures. BMC Bioinformatics. 24(1). 292–292. 1 indexed citations
6.
Yuan, Peng, Лей Тонг, Thomas M. Morse, et al.. (2022). PLD3 affects axonal spheroids and network defects in Alzheimer’s disease. Nature. 612(7939). 328–337. 76 indexed citations
7.
Kumbhar, Pramod, Salvador Durá-Bernal, James King, et al.. (2022). Modernizing the NEURON Simulator for Sustainability, Portability, and Performance. Frontiers in Neuroinformatics. 16. 884046–884046. 22 indexed citations
8.
Huertas, Marco A., et al.. (2022). Conditions for Synaptic Specificity during the Maintenance Phase of Synaptic Plasticity. eNeuro. 9(3). ENEURO.0064–22.2022. 3 indexed citations
9.
Neymotin, Samuel A., Blake Caldwell, Robert A. McDougal, et al.. (2020). Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data. eLife. 9. 65 indexed citations
10.
Durá-Bernal, Salvador, Benjamin A. Suter, Padraig Gleeson, et al.. (2019). NetPyNE, a tool for data-driven multiscale modeling of brain circuits. eLife. 8. 88 indexed citations
11.
Tropper, Carl, et al.. (2016). Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons. ACM Transactions on Modeling and Computer Simulation. 27(2). 1–27. 8 indexed citations
12.
McDougal, Robert A., Thomas M. Morse, Ted Carnevale, et al.. (2016). Twenty years of ModelDB and beyond: building essential modeling tools for the future of neuroscience. Journal of Computational Neuroscience. 42(1). 1–10. 126 indexed citations
13.
Marenco, Luis, Rixin Wang, Robert A. McDougal, et al.. (2016). ORDB, HORDE, ODORactor and other on-line knowledge resources of olfactory receptor-odorant interactions. Database. 2016. baw132–baw132. 15 indexed citations
14.
Lytton, William W., et al.. (2016). Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON. Neural Computation. 28(10). 2063–2090. 25 indexed citations
15.
McDougal, Robert A., Thomas M. Morse, Michael L. Hines, & Gordon M. Shepherd. (2015). ModelView for ModelDB: Online Presentation of Model Structure. Neuroinformatics. 13(4). 459–470. 12 indexed citations
16.
McDougal, Robert A. & Gordon M. Shepherd. (2015). 3D-printer visualization of neuron models. Frontiers in Neuroinformatics. 9. 18–18. 20 indexed citations
17.
Tropper, Carl, et al.. (2014). Neuron time warp. Winter Simulation Conference. 3447–3458. 6 indexed citations
18.
McDougal, Robert A., Michael L. Hines, & William W. Lytton. (2013). Reaction-diffusion in the NEURON simulator. Frontiers in Neuroinformatics. 7. 28–28. 39 indexed citations
19.
McDougal, Robert A., Michael L. Hines, & William W. Lytton. (2013). Water-tight membranes from neuronal morphology files. Journal of Neuroscience Methods. 220(2). 167–178. 12 indexed citations
20.
McDougal, Robert A.. (2011). Excitatory-Inhibitory Interactions as the Basis of Working Memory. OhioLink ETD Center (Ohio Library and Information Network). 2 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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