Jenna M. Sullivan

556 total citations
18 papers, 426 citations indexed

About

Jenna M. Sullivan is a scholar working on Cellular and Molecular Neuroscience, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Jenna M. Sullivan has authored 18 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 8 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Molecular Biology. Recurrent topics in Jenna M. Sullivan's work include Medical Imaging Techniques and Applications (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Receptor Mechanisms and Signaling (4 papers). Jenna M. Sullivan is often cited by papers focused on Medical Imaging Techniques and Applications (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Receptor Mechanisms and Signaling (4 papers). Jenna M. Sullivan collaborates with scholars based in United States and Denmark. Jenna M. Sullivan's co-authors include Evan D. Morris, Kelly Cosgrove, David Labaree, Richard E. Carson, Hong Gao, Sujin Kim, Su Kim, Nabeel Nabulsi, Erin McGovern and Hemant D. Tagare and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and Neurology.

In The Last Decade

Jenna M. Sullivan

16 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jenna M. Sullivan United States 9 168 147 100 80 76 18 426
Ricky R. Savjani United States 11 115 0.7× 126 0.9× 57 0.6× 146 1.8× 183 2.4× 39 478
Dustin Wooten United States 16 205 1.2× 173 1.2× 194 1.9× 92 1.1× 103 1.4× 45 682
José Anton‐Rodriguez United Kingdom 12 73 0.4× 168 1.1× 65 0.7× 67 0.8× 96 1.3× 34 726
William E. Wu United States 8 88 0.5× 170 1.2× 166 1.7× 92 1.1× 108 1.4× 20 627
Sudha Garg United States 15 235 1.4× 216 1.5× 279 2.8× 75 0.9× 101 1.3× 35 754
Elena Prodi Italy 9 63 0.4× 74 0.5× 72 0.7× 67 0.8× 42 0.6× 22 371
Franziska Stöber Germany 8 85 0.5× 55 0.4× 82 0.8× 38 0.5× 45 0.6× 10 322
Krista Fowles United States 12 188 1.1× 81 0.6× 137 1.4× 91 1.1× 39 0.5× 26 463
Terry Brown United States 10 214 1.3× 138 0.9× 111 1.1× 112 1.4× 23 0.3× 13 587
Colm J. McGinnity United Kingdom 15 141 0.8× 256 1.7× 76 0.8× 81 1.0× 22 0.3× 43 558

Countries citing papers authored by Jenna M. Sullivan

Since Specialization
Citations

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

Fields of papers citing papers by Jenna M. Sullivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jenna M. Sullivan

This figure shows the co-authorship network connecting the top 25 collaborators of Jenna M. Sullivan. A scholar is included among the top collaborators of Jenna M. Sullivan 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 Jenna M. Sullivan. Jenna M. Sullivan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Nirschl, Christopher J., Daniel J. Hicklin, Nesreen S. Ismail, et al.. (2022). Abstract 2054: WTX-124 is a novel IL-2 pro-drug that is conditionally activated in tumors and drives anti-tumor immunity by activating tumor infiltrating CD8+ T cells. Cancer Research. 82(12_Supplement). 2054–2054.
2.
Hardy, Larry W., Jenna M. Sullivan, Noel A. Powell, et al.. (2020). Functional deficit in hippocampal activity during fear extinction recall in the single prolonged-stress model of PTSD in male rats. Behavioural Brain Research. 396. 112902–112902. 5 indexed citations
3.
Sullivan, Jenna M., et al.. (2019). SPECT Imaging of Muscle Injury with [99mTc]MDP in a Mouse Model of Muscular Dystrophy. Molecular Imaging and Biology. 22(3). 562–568. 2 indexed citations
4.
Kang, Yeona, P. David Mozley, Ajay Verma, et al.. (2018). Noninvasive PK11195‐PET Image Analysis Techniques Can Detect Abnormal Cerebral Microglial Activation in Parkinson's Disease. Journal of Neuroimaging. 28(5). 496–505. 28 indexed citations
5.
Swayze, Eric E., Berit Powers, Fredrik Kamme, et al.. (2016). Kinetics of ASO Distribution and Pharmacodynamics in the CNS after an Intrathecal Bolus Dose in Rat (S38.008). Neurology. 86(16_supplement). 1 indexed citations
6.
Park, Eunkyung, Jenna M. Sullivan, Beata Planeta, et al.. (2015). Test–retest reproducibility of the metabotropic glutamate receptor 5 ligand [18F]FPEB with bolus plus constant infusion in humans. European Journal of Nuclear Medicine and Molecular Imaging. 42(10). 1530–1541. 33 indexed citations
7.
Cosgrove, Kelly, Sujin Kim, Erin McGovern, et al.. (2014). Sex Differences in the Brain's Dopamine Signature of Cigarette Smoking. Journal of Neuroscience. 34(50). 16851–16855. 137 indexed citations
8.
9.
Sullivan, Jenna M., Su Kim, Kelly Cosgrove, & Evan D. Morris. (2013). Limitations of SRTM, Logan graphical method, and equilibrium analysis for measuring transient dopamine release with [(11)C]raclopride PET.. PubMed. 3(3). 247–60. 17 indexed citations
10.
Morris, Evan D., Su Kim, Jenna M. Sullivan, et al.. (2013). Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking. Journal of Visualized Experiments. 14 indexed citations
11.
Sullivan, Jenna M., et al.. (2013). Quantitative Analysis of [11C]-Erlotinib PET Demonstrates Specific Binding for Activating Mutations of the EGFR Kinase Domain. Neoplasia. 15(12). 1347–1353. 35 indexed citations
12.
Morris, Evan D., Su Kim, Jenna M. Sullivan, et al.. (2013). Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking. Journal of Visualized Experiments. 2 indexed citations
13.
Olesen, Oline V., Jenna M. Sullivan, Tim Mulnix, et al.. (2012). List-Mode PET Motion Correction Using Markerless Head Tracking: Proof-of-Concept With Scans of Human Subject. IEEE Transactions on Medical Imaging. 32(2). 200–209. 52 indexed citations
14.
Sullivan, Jenna M., Keunpoong Lim, David Labaree, et al.. (2012). Kinetic Analysis of the Metabotropic Glutamate Subtype 5 Tracer [18F]FPEB in Bolus and Bolus-Plus-Constant-Infusion Studies in Humans. Journal of Cerebral Blood Flow & Metabolism. 33(4). 532–541. 56 indexed citations
15.
Sullivan, Jenna M., Shannon L. Risacher, Marc D. Normandin, et al.. (2011). Imaging of alcohol‐induced dopamine release in rats:Preliminary findings with [11C]raclopride PET. Synapse. 65(9). 929–937. 5 indexed citations
16.
Sullivan, Jenna M., Shannon L. Risacher, Marc D. Normandin, et al.. (2011). Imaging of Alcohol-Induced Dopamine Release in Rats: Preliminary Findings With (. 1 indexed citations
17.
Sullivan, Jenna M., Keunpoong Lim, David Labaree, et al.. (2011). Bolus vs. bolus/infusion of the mGluR5 tracer [18F]FPEB in humans. 52. 9–9. 1 indexed citations
18.
Sullivan, Jenna M., Keunpoong Lim, Shu-fei Lin, et al.. (2010). Kinetic modeling of the mGluR5 tracer [18F]F-FPEB in humans. NeuroImage. 52. S169–S170. 1 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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