Pamela L Shaw

2.7k total citations · 1 hit paper
21 papers, 2.1k citations indexed

About

Pamela L Shaw is a scholar working on Public Health, Environmental and Occupational Health, Pharmacology and Computational Theory and Mathematics. According to data from OpenAlex, Pamela L Shaw has authored 21 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Public Health, Environmental and Occupational Health, 4 papers in Pharmacology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Pamela L Shaw's work include Computational Drug Discovery Methods (4 papers), Cholinesterase and Neurodegenerative Diseases (4 papers) and Trauma and Emergency Care Studies (4 papers). Pamela L Shaw is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Cholinesterase and Neurodegenerative Diseases (4 papers) and Trauma and Emergency Care Studies (4 papers). Pamela L Shaw collaborates with scholars based in United States and Brazil. Pamela L Shaw's co-authors include Marsel Mesulam, Sandra Weıntraub, Deborah C. Mash, M.‐Marsel Mesulam, Allan I. Levey, Oksana Lockridge, Ellen G. Duysen, Bruce Quinn, Eileen H. Bigio and M.‐Marsel Mesulam and has published in prestigious journals such as Annals of Neurology, Neuroscience and Journal of Neurochemistry.

In The Last Decade

Pamela L Shaw

20 papers receiving 2.0k citations

Hit Papers

Acetylcholinesterase knockouts establish central choliner... 2002 2026 2010 2018 2002 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pamela L Shaw United States 14 857 743 471 446 288 21 2.1k
Taher Darreh‐Shori Sweden 31 1.2k 1.5× 886 1.2× 622 1.3× 757 1.7× 305 1.1× 75 2.4k
Aaron Ritter United States 15 630 0.7× 1.2k 1.7× 383 0.8× 556 1.2× 252 0.9× 44 2.4k
R. Anand India 17 469 0.5× 491 0.7× 161 0.3× 348 0.8× 222 0.8× 41 2.0k
Enrica Cavedo France 16 592 0.7× 1.1k 1.5× 250 0.5× 622 1.4× 307 1.1× 24 2.7k
Arti Singh India 19 596 0.7× 794 1.1× 228 0.5× 869 1.9× 298 1.0× 79 2.5k
Robert Lai United Kingdom 25 614 0.7× 1.6k 2.2× 327 0.7× 675 1.5× 364 1.3× 61 2.7k
Abdullah Al Mamun Bangladesh 27 518 0.6× 947 1.3× 220 0.5× 798 1.8× 193 0.7× 63 2.4k
Kinga Sałat Poland 27 548 0.6× 613 0.8× 258 0.5× 722 1.6× 577 2.0× 110 2.4k
R. H. Perry United Kingdom 20 579 0.7× 848 1.1× 236 0.5× 667 1.5× 529 1.8× 30 2.9k

Countries citing papers authored by Pamela L Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Pamela L Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pamela L Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of Pamela L Shaw. A scholar is included among the top collaborators of Pamela L Shaw 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 Pamela L Shaw. Pamela L Shaw 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.
Carson, Matthew B., et al.. (2022). Bridging the gap: A library‐based collaboration to enhance data skills for clinical researchers. Learning Health Systems. 7(2). e10339–e10339. 2 indexed citations
2.
Fort, Daniel, et al.. (2017). Mapping the evolving definitions of translational research. Journal of Clinical and Translational Science. 1(1). 60–66. 104 indexed citations
3.
Paladino, Lorenzo, et al.. (2016). Surgical and trauma care in low- and middle-income countries: a review of capacity assessments. Journal of Surgical Research. 210. 139–151. 31 indexed citations
4.
Clare, Susan E. & Pamela L Shaw. (2016). “Big Data” for breast cancer: where to look and what you will find. npj Breast Cancer. 2(1). 13 indexed citations
5.
Shaw, Pamela L, et al.. (2015). Data Management Practices Across an Institution: Survey and Report. Journal of Librarianship and Scholarly Communication. 3(2). 1225–1225. 43 indexed citations
6.
Paladino, Lorenzo, et al.. (2015). Surgical and Trauma Care in Low- and Middle-Income Countries: A Systematic Review of Tools to Evaluate Capacity. Journal of the American College of Surgeons. 221(4). S88–S88.
7.
Richards, Christopher T., et al.. (2014). Trauma system development in low- and middle-income countries: a review. Journal of Surgical Research. 193(1). 300–307. 65 indexed citations
8.
Richards, Christopher T., et al.. (2014). Layperson trauma training in low- and middle-income countries: a review. Journal of Surgical Research. 190(1). 104–110. 52 indexed citations
9.
Feng, Gang, Pamela L Shaw, Steven T. Rosen, Simon Lin, & Warren A. Kibbe. (2011). Using the Bioconductor GeneAnswers Package to Interpret Gene Lists. Methods in molecular biology. 802. 101–112. 20 indexed citations
10.
Falk-Krzesinski, Holly J., et al.. (2010). Comparative matrix of research networking tools. 1 indexed citations
11.
Shaw, Pamela L, Austin N. Kirschner, Theodore S. Jardetzky, & Richard Longnecker. (2010). Characteristics of Epstein–Barr virus envelope protein gp42. Virus Genes. 40(3). 307–319. 15 indexed citations
12.
Shaw, Pamela L. (2010). Diversity training: a DVD resource showcasing BME role models.. PubMed. 83(12). 30–3. 3 indexed citations
13.
Lambert, Mary P., Pauline T. Velasco, Lei Chang, et al.. (2006). Monoclonal antibodies that target pathological assemblies of Aβ. Journal of Neurochemistry. 100(1). 23–35. 274 indexed citations
14.
Shaw, Pamela L, et al.. (2006). Locus coeruleus neurofibrillary degeneration in aging, mild cognitive impairment and early Alzheimer's disease. Neurobiology of Aging. 28(3). 327–335. 304 indexed citations
15.
Mesulam, Marsel, Pamela L Shaw, Deborah C. Mash, & Sandra Weıntraub. (2004). Cholinergic nucleus basalis tauopathy emerges early in the aging‐MCI‐AD continuum. Annals of Neurology. 55(6). 815–828. 288 indexed citations
16.
Mesulam, M.‐Marsel, et al.. (2002). Acetylcholinesterase knockouts establish central cholinergic pathways and can use butyrylcholinesterase to hydrolyze acetylcholine. Neuroscience. 110(4). 627–639. 549 indexed citations breakdown →
17.
Mesulam, Marsel, et al.. (2002). Widely Spread Butyrylcholinesterase Can Hydrolyze Acetylcholine in the Normal and Alzheimer Brain. Neurobiology of Disease. 9(1). 88–93. 268 indexed citations
18.
Hogan, Thomas P., et al.. (1996). Use of Fetal Cortical Grafts in Hypoxic-Ischemic Brain Injury in Neonatal Rats. Experimental Neurology. 137(1). 127–141. 18 indexed citations
19.
Schulz, Mette Katrine, John A. McNulty, Robert J. Handa, et al.. (1995). Fetal Neocortical Transplants Grafted into Neocortical Lesion Cavities Made in Newborn Rats: An Analysis of Transplant Integration with the Host Brain. Cell Transplantation. 4(1). 123–132. 3 indexed citations
20.
McNulty, John A., Linda M. Fox, Pamela L Shaw, et al.. (1991). Pineal Gland Transplants into the Cerebral Hemisphere of Newborn Rats: A Study of the Blood Brain Barrier and Innervation. Neural Plasticity. 2(2). 113–124. 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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