Elizabeth A. Eckman

4.9k total citations · 1 hit paper
40 papers, 3.9k citations indexed

About

Elizabeth A. Eckman is a scholar working on Physiology, Molecular Biology and Pharmacology. According to data from OpenAlex, Elizabeth A. Eckman has authored 40 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Physiology, 14 papers in Molecular Biology and 11 papers in Pharmacology. Recurrent topics in Elizabeth A. Eckman's work include Alzheimer's disease research and treatments (28 papers), Cholinesterase and Neurodegenerative Diseases (11 papers) and Cellular transport and secretion (6 papers). Elizabeth A. Eckman is often cited by papers focused on Alzheimer's disease research and treatments (28 papers), Cholinesterase and Neurodegenerative Diseases (11 papers) and Cellular transport and secretion (6 papers). Elizabeth A. Eckman collaborates with scholars based in United States, Germany and Canada. Elizabeth A. Eckman's co-authors include Christopher B. Eckman, Rudolph E. Tanzi, Suzanne Y. Guénette, Wesley Farris, Dennis J. Selkoe, Yang Chang, Loren Lindsley, Matthew P. Frosch, Dana Kim Reed and Javier Pacheco‐Quinto and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Elizabeth A. Eckman

40 papers receiving 3.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Insulin-degrading enzyme regulates the levels of insulin, amyloid β-protein, and the β-amyloid precursor protein intracellular domain in vivo

2003 1.2k citations Wesley Farris, Yang Chang et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elizabeth A. Eckman United States	24	2.6k	1.6k	644	611	577	40	3.9k
Alfredo Lorenzo Argentina	22	3.1k 1.2×	2.1k 1.3×	776 1.2×	582 1.0×	874 1.5×	35	4.6k
Etsuro Matsubara Japan	33	2.9k 1.1×	1.7k 1.0×	498 0.8×	694 1.1×	735 1.3×	128	4.4k
Wesley Farris United States	10	1.9k 0.7×	987 0.6×	485 0.8×	414 0.7×	416 0.7×	11	2.7k
Dora M. Kovacs United States	31	3.0k 1.1×	2.7k 1.7×	762 1.2×	464 0.8×	932 1.6×	56	5.2k
Roberta Borghi Italy	25	2.0k 0.7×	1.2k 0.7×	606 0.9×	407 0.7×	468 0.8×	49	3.2k
Tiziana Borsello Italy	31	1.5k 0.6×	2.1k 1.3×	482 0.7×	742 1.2×	1.2k 2.1×	82	4.1k
Stephan Schilling Germany	32	2.1k 0.8×	1.7k 1.0×	516 0.8×	429 0.7×	618 1.1×	61	3.7k
Irene H. Cheng United States	25	2.6k 1.0×	1.5k 0.9×	805 1.3×	601 1.0×	999 1.7×	53	4.1k
Troy T. Rohn United States	36	2.2k 0.8×	1.9k 1.2×	553 0.9×	633 1.0×	942 1.6×	76	4.1k
Claudio Russo Italy	31	1.8k 0.7×	2.0k 1.3×	482 0.7×	425 0.7×	506 0.9×	91	3.5k

Countries citing papers authored by Elizabeth A. Eckman

Since Specialization

Citations

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

Fields of papers citing papers by Elizabeth A. Eckman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elizabeth A. Eckman

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

All Works

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20 of 20 papers shown

Peng, Hui, et al.. (2023). Brain Targeted AAV1-GALC Gene Therapy Reduces Psychosine and Extends Lifespan in a Mouse Model of Krabbe Disease. Genes. 14(8). 1517–1517. 5 indexed citations

Eckman, Elizabeth A., et al.. (2023). Nascent Aβ42 Fibrillization in Synaptic Endosomes Precedes Plaque Formation in a Mouse Model of Alzheimer's-like β-Amyloidosis. Journal of Neuroscience. 43(50). 8812–8824. 6 indexed citations

Pacheco‐Quinto, Javier, Christopher B. Eckman, & Elizabeth A. Eckman. (2016). Major amyloid-β–degrading enzymes, endothelin-converting enzyme-2 and neprilysin, are expressed by distinct populations of GABAergic interneurons in hippocampus and neocortex. Neurobiology of Aging. 48. 83–92. 32 indexed citations

Padmaraju, Vasudevaraju, Javier Pacheco‐Quinto, Craig E. Crosson, et al.. (2014). Evidence of a Novel Mechanism for Partial γ-Secretase Inhibition Induced Paradoxical Increase in Secreted Amyloid β Protein. PLoS ONE. 9(3). e91531–e91531. 16 indexed citations

Pacheco‐Quinto, Javier & Elizabeth A. Eckman. (2013). Endothelin-converting Enzymes Degrade Intracellular β-Amyloid Produced within the Endosomal/Lysosomal Pathway and Autophagosomes*. Journal of Biological Chemistry. 288(8). 5606–5615. 77 indexed citations

Suh, Jaehong, Alvin W. Lyckman, Lirong Wang, Elizabeth A. Eckman, & Suzanne Y. Guénette. (2011). FE65 proteins regulate NMDA receptor activation‐induced amyloid precursor protein processing. Journal of Neurochemistry. 119(2). 377–388. 16 indexed citations

Lee, Chris W., et al.. (2010). Molecular Characterization of Mutations That Cause Globoid Cell Leukodystrophy and Pharmacological Rescue Using Small Molecule Chemical Chaperones. Journal of Neuroscience. 30(16). 5489–5497. 73 indexed citations

Hanna, Amanda, Patrick Horne, Debra Yager, et al.. (2009). Amyloid β and impairment in multiple memory systems in older transgenic APP TgCRND8 mice. Genes Brain & Behavior. 8(7). 676–684. 19 indexed citations

Eckman, Elizabeth A., Frederick J. Troendle, Abdul H. Fauq, et al.. (2006). Regulation of Steady-state β-Amyloid Levels in the Brain by Neprilysin and Endothelin-converting Enzyme but Not Angiotensin-converting Enzyme. Journal of Biological Chemistry. 281(41). 30471–30478. 165 indexed citations

10.

Eckman, Chris, Cláudia G. Almeida, Douglas L. Feinstein, et al.. (2004). Live discussion: Amyloid-β degradation: The forgotten half of Alzheimer's disease1. Journal of Alzheimer s Disease. 5(6). 491–497. 2 indexed citations

11.

Farris, Wesley, Malcolm A. Leissring, Elizabeth A. Eckman, et al.. (2004). Partial Loss-of-Function Mutations in Insulin-Degrading Enzyme that Induce Diabetes also Impair Degradation of Amyloid β-Protein. American Journal Of Pathology. 164(4). 1425–1434. 202 indexed citations

12.

Farris, Wesley, Yang Chang, Loren Lindsley, et al.. (2003). Insulin-degrading enzyme regulates the levels of insulin, amyloid β-protein, and the β-amyloid precursor protein intracellular domain in vivo. Proceedings of the National Academy of Sciences. 100(7). 4162–4167. 1191 indexed citations breakdown →

13.

Chang, Yang, Giuseppina Tesco, William Jeong, et al.. (2003). Generation of the β-Amyloid Peptide and the Amyloid Precursor Protein C-terminal Fragment γ Are Potentiated by FE65L1. Journal of Biological Chemistry. 278(51). 51100–51107. 64 indexed citations

14.

Eckman, Elizabeth A., et al.. (2003). Alzheimer's Disease β-Amyloid Peptide Is Increased in Mice Deficient in Endothelin-converting Enzyme. Journal of Biological Chemistry. 278(4). 2081–2084. 215 indexed citations

15.

Yager, Debra, et al.. (2002). Natural product extracts that reduce accumulation of the alzheimer’s amyloid β peptide. Journal of Molecular Neuroscience. 19(1-2). 129–133. 13 indexed citations

16.

Eckman, Elizabeth A., Dana Kim Reed, & Christopher B. Eckman. (2001). Degradation of the Alzheimer's Amyloid β Peptide by Endothelin-converting Enzyme. Journal of Biological Chemistry. 276(27). 24540–24548. 277 indexed citations

17.

Haugabook, Sharie J., Debra Yager, Elizabeth A. Eckman, et al.. (2001). High throughput screens for the identification of compounds that alter the accumulation of the Alzheimer's amyloid β peptide (Aβ). Journal of Neuroscience Methods. 108(2). 171–179. 35 indexed citations

18.

Ferkol, Thomas W., et al.. (2000). Transport of Bifunctional Proteins Across Respiratory Epithelial Cells via the Polymeric Immunoglobulin Receptor. American Journal of Respiratory and Critical Care Medicine. 161(3). 944–951. 17 indexed citations

19.

Eckman, Elizabeth A., William D. Mallender, T. Szegletes, et al.. (1999). In Vitro Transport of Active α1-Antitrypsin to the Apical Surface of Epithelia by Targeting the Polymeric Immunoglobulin Receptor. American Journal of Respiratory Cell and Molecular Biology. 21(2). 246–252. 13 indexed citations

20.

Branchini, Bruce R., et al.. (1995). Modification of Chloride Ion Transport in Human Erythrocyte Ghost Membranes by Photoaffinity Labeling Reagents Based on the Structure of 5-Nitro-2-(3-Phenylpropylamino)-benzoic Acid (NPPB). Archives of Biochemistry and Biophysics. 318(1). 221–230. 3 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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