Jenna L. Pappalardo

409 total citations
9 papers, 213 citations indexed

About

Jenna L. Pappalardo is a scholar working on Immunology, Neurology and Molecular Biology. According to data from OpenAlex, Jenna L. Pappalardo has authored 9 papers receiving a total of 213 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 4 papers in Neurology and 2 papers in Molecular Biology. Recurrent topics in Jenna L. Pappalardo's work include Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Amyotrophic Lateral Sclerosis Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Jenna L. Pappalardo is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Amyotrophic Lateral Sclerosis Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Jenna L. Pappalardo collaborates with scholars based in United States, Japan and Switzerland. Jenna L. Pappalardo's co-authors include David A. Hafler, Chrysoula Zografou, Andrés Rojas, Kathryn Miller‐Jensen, Jennifer Chiarella, Serena Spudich, Richard W. Price, Shelli Farhadian, Kevin A. Robertson and Sameet Mehta and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and The Journal of Immunology.

In The Last Decade

Jenna L. Pappalardo

7 papers receiving 213 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jenna L. Pappalardo United States	3	119	93	78	38	25	9	213
Derek Atkinson Belgium	8	55 0.5×	15 0.2×	105 1.3×	61 1.6×	13 0.5×	13	227
Omkar Chaudhary United States	7	66 0.6×	25 0.3×	35 0.4×	49 1.3×	4 0.2×	13	211
Catherine R. Cochrane Australia	9	34 0.3×	45 0.5×	229 2.9×	97 2.6×	30 1.2×	11	396
Kayo Kondo United States	8	115 1.0×	20 0.2×	27 0.3×	8 0.2×	12 0.5×	13	184
Wesley M. Marin United States	10	269 2.3×	27 0.3×	43 0.6×	6 0.2×	7 0.3×	15	357
Hector Huerga Encabo United Kingdom	10	138 1.2×	16 0.2×	86 1.1×	7 0.2×	5 0.2×	14	295
Eike Kienle Germany	7	32 0.3×	14 0.2×	160 2.1×	12 0.3×	9 0.4×	10	283
Qingyong Ji United States	8	275 2.3×	57 0.6×	58 0.7×	4 0.1×	76 3.0×	9	361
Corey M. Williams United States	6	147 1.2×	11 0.1×	184 2.4×	15 0.4×	4 0.2×	11	310
Patrick Meylan Switzerland	6	40 0.3×	25 0.3×	162 2.1×	3 0.1×	9 0.4×	6	356

Countries citing papers authored by Jenna L. Pappalardo

Since Specialization

Citations

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

Fields of papers citing papers by Jenna L. Pappalardo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jenna L. Pappalardo

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

All Works

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9 of 9 papers shown

1.

Wei, Jessica, Jeonghyeon Moon, Yoshiaki Yasumizu, et al.. (2025). Transcriptomic profiling after B cell depletion reveals central and peripheral immune cell changes in multiple sclerosis. Journal of Clinical Investigation. 135(11). 2 indexed citations

2.

Jin, Ke, Jenna L. Pappalardo, Soonweng Cho, et al.. (2025). Harnessing CD39 inhibition to boost antitumor immunity with extracellular ATP. The Journal of Immunology. 214(11). 2906–2918.

3.

Huang, Julie Y., Robert Paul, Felix L. Yeh, et al.. (2022). A Phase 2 Study of AL001 in Frontotemporal Dementia Patients Carrying a Granulin Mutation (P5-3.005). Neurology. 98(18_supplement). 2 indexed citations

4.

Rojas, Andrés, et al.. (2021). Co-stimulation with opposing macrophage polarization cues leads to orthogonal secretion programs in individual cells. Nature Communications. 12(1). 301–301. 49 indexed citations

5.

Jackson, Sam, Felix L. Yeh, Michael E. Ward, et al.. (2021). Six months interim analysis of the phase 2 study of AL001 in frontotemporal dementia patients carrying a granulin mutation. Alzheimer s & Dementia. 17(S9). 1 indexed citations

6.

Pappalardo, Jenna L., Le Zhang, Kelly Perlman, et al.. (2020). Transcriptomic and clonal characterization of T cells in the human central nervous system. Science Immunology. 5(51). 78 indexed citations

7.

Farhadian, Shelli, Sameet Mehta, Chrysoula Zografou, et al.. (2018). Single-cell RNA sequencing reveals microglia-like cells in cerebrospinal fluid during virologically suppressed HIV. JCI Insight. 3(18). 79 indexed citations

8.

Amodio, Matthew, et al.. (2018). Neuron Interference: Evidence-Based Batch Effect Removal. arXiv (Cornell University). 2 indexed citations

9.

Pappalardo, Jenna L. & Kevin C. O’Connor. (2018). B cells drive auto-T cells to the brain. Science Immunology. 3(28).

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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