Megan E. McLellan

1.6k total citations
6 papers, 1.2k citations indexed

About

Megan E. McLellan is a scholar working on Physiology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Megan E. McLellan has authored 6 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Physiology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Computational Theory and Mathematics. Recurrent topics in Megan E. McLellan's work include Alzheimer's disease research and treatments (6 papers), Computational Drug Discovery Methods (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). Megan E. McLellan is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Computational Drug Discovery Methods (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). Megan E. McLellan collaborates with scholars based in United States. Megan E. McLellan's co-authors include Stephen T. Kajdasz, Brian J. Bacskai, Bradley T. Hyman, William E. Klunk, Chester A. Mathis, Yanming Wang, Daniel P. Holt, Matthew P. Frosch, Manik L. Debnath and Dale Schenk and has published in prestigious journals such as Journal of Neuroscience, Journal of Neuropathology & Experimental Neurology and Bioorganic & Medicinal Chemistry Letters.

In The Last Decade

Megan E. McLellan

6 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Megan E. McLellan United States	6	969	366	359	239	217	6	1.2k
Andrea Pfeifer Switzerland	18	979 1.0×	251 0.7×	458 1.3×	225 0.9×	259 1.2×	51	1.4k
Lee‐Way Jin United States	21	1.0k 1.1×	424 1.2×	690 1.9×	324 1.4×	127 0.6×	39	1.7k
Anna Lord Sweden	15	869 0.9×	208 0.6×	444 1.2×	263 1.1×	219 1.0×	15	1.2k
Janice Kurth United States	13	1.2k 1.2×	288 0.8×	707 2.0×	498 2.1×	184 0.8×	20	2.3k
Akihiko Koyama United States	13	1.0k 1.1×	285 0.8×	421 1.2×	465 1.9×	155 0.7×	24	1.8k
Sethu Sankaranarayanan United States	21	764 0.8×	312 0.9×	479 1.3×	280 1.2×	169 0.8×	38	1.4k
Claudia Prada United States	10	1.2k 1.2×	577 1.6×	537 1.5×	375 1.6×	130 0.6×	10	1.7k
Stephen T. Kajdasz United States	12	1.6k 1.6×	656 1.8×	638 1.8×	435 1.8×	353 1.6×	15	2.2k
Vicki Betts Ireland	10	933 1.0×	215 0.6×	583 1.6×	286 1.2×	188 0.9×	11	1.3k
Pär Gellerfors Sweden	25	999 1.0×	202 0.6×	1.2k 3.3×	279 1.2×	265 1.2×	43	2.0k

Countries citing papers authored by Megan E. McLellan

Since Specialization

Citations

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

Fields of papers citing papers by Megan E. McLellan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Megan E. McLellan. 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 Megan E. McLellan. The network helps show where Megan E. McLellan may publish in the future.

Co-authorship network of co-authors of Megan E. McLellan

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

All Works

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6 of 6 papers shown

Kajdasz, Stephen T., et al.. (2003). In Vivo Multiphoton Imaging of a Transgenic Mouse Model of Alzheimer Disease Reveals Marked Thioflavine-S-Associated Alterations in Neurite Trajectories. Journal of Neuropathology & Experimental Neurology. 62(2). 137–145. 83 indexed citations

Stern, Edward A., Megan E. McLellan, Stephen T. Kajdasz, et al.. (2003). Amyloid-β Antibody Treatment Leads to Rapid Normalization of Plaque-Induced Neuritic Alterations. Journal of Neuroscience. 23(34). 10879–10883. 129 indexed citations

McLellan, Megan E., Stephen T. Kajdasz, Bradley T. Hyman, & Brian J. Bacskai. (2003). In VivoImaging of Reactive Oxygen Species Specifically Associated with Thioflavine S-Positive Amyloid Plaques by Multiphoton Microscopy. Journal of Neuroscience. 23(6). 2212–2217. 138 indexed citations

Klunk, William E., Brian J. Bacskai, Chester A. Mathis, et al.. (2002). Imaging Aβ Plaques in Living Transgenic Mice with Multiphoton Microscopy and Methoxy-X04, a Systemically Administered Congo Red Derivative. Journal of Neuropathology & Experimental Neurology. 61(9). 797–805. 320 indexed citations

Mathis, Chester A., Brian J. Bacskai, Stephen T. Kajdasz, et al.. (2002). A lipophilic thioflavin-T derivative for positron emission tomography (PET) imaging of amyloid in brain. Bioorganic & Medicinal Chemistry Letters. 12(3). 295–298. 282 indexed citations

Bacskai, Brian J., Stephen T. Kajdasz, Megan E. McLellan, et al.. (2002). Non-Fc-Mediated Mechanisms Are Involved in Clearance of Amyloid-βIn Vivoby Immunotherapy. Journal of Neuroscience. 22(18). 7873–7878. 270 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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