Marc E. Weksler

9.3k total citations
191 papers, 7.6k citations indexed

About

Marc E. Weksler is a scholar working on Immunology, Molecular Biology and Physiology. According to data from OpenAlex, Marc E. Weksler has authored 191 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Immunology, 35 papers in Molecular Biology and 30 papers in Physiology. Recurrent topics in Marc E. Weksler's work include T-cell and B-cell Immunology (80 papers), Immune Cell Function and Interaction (61 papers) and Immunotherapy and Immune Responses (36 papers). Marc E. Weksler is often cited by papers focused on T-cell and B-cell Immunology (80 papers), Immune Cell Function and Interaction (61 papers) and Immunotherapy and Immune Responses (36 papers). Marc E. Weksler collaborates with scholars based in United States, France and United Kingdom. Marc E. Weksler's co-authors include Paul Szabo, J B Innes, Robert W. Kozak, T. H. Hütteroth, R. Schwab, Norman Relkin, Charles E. Moody, Gregory W. Siskind, Marco Durante and Steven Gillis and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Marc E. Weksler

188 papers receiving 7.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marc E. Weksler United States	49	4.0k	1.4k	1.4k	953	760	191	7.6k
S. M. Wolff United States	30	3.7k 0.9×	2.1k 1.5×	650 0.5×	1.4k 1.5×	577 0.8×	66	8.2k
Daniela N. Männel Germany	44	4.8k 1.2×	2.6k 1.8×	931 0.7×	842 0.9×	319 0.4×	145	9.1k
Domenico Lio Italy	48	2.4k 0.6×	1.8k 1.3×	1.6k 1.1×	1.3k 1.3×	260 0.3×	176	7.3k
J. Vidya Sarma United States	46	4.3k 1.1×	1.8k 1.3×	579 0.4×	1.4k 1.5×	436 0.6×	74	7.7k
Stephen M. Anderton United Kingdom	46	6.0k 1.5×	2.5k 1.8×	676 0.5×	607 0.6×	653 0.9×	120	10.1k
Pam Fredman Sweden	51	1.4k 0.3×	4.3k 3.0×	1.7k 1.3×	557 0.6×	799 1.1×	177	8.0k
Luigi Varesio Italy	49	3.7k 0.9×	3.0k 2.1×	743 0.5×	608 0.6×	216 0.3×	199	8.4k
Catherine Uyttenhove Belgium	46	6.8k 1.7×	2.3k 1.6×	823 0.6×	773 0.8×	468 0.6×	105	10.3k
Andrew Chow United States	38	4.1k 1.0×	2.1k 1.5×	735 0.5×	1.1k 1.1×	448 0.6×	108	8.6k
Brian M. J. Foxwell United Kingdom	46	3.2k 0.8×	2.6k 1.8×	418 0.3×	727 0.8×	273 0.4×	106	7.5k

Countries citing papers authored by Marc E. Weksler

Since Specialization

Citations

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

Fields of papers citing papers by Marc E. Weksler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marc E. Weksler

This figure shows the co-authorship network connecting the top 25 collaborators of Marc E. Weksler. A scholar is included among the top collaborators of Marc E. Weksler 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 Marc E. Weksler. Marc E. Weksler 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

Lescale, Chloé, Sheila Dias, Ana Cumano, et al.. (2010). Reduced EBF expression underlies loss of B‐cell potential of hematopoietic progenitors with age. Aging Cell. 9(3). 410–419. 48 indexed citations

Szabo, Paul, Norman Relkin, & Marc E. Weksler. (2008). Natural human antibodies to amyloid beta peptide. Autoimmunity Reviews. 7(6). 415–420. 91 indexed citations

Shen, Steven S., et al.. (2005). Effect of age on thymic development, T cell immunity, and helper T cell function. Reviews of physiology, biochemistry and pharmacology. 139. 123–139. 5 indexed citations

Weksler, Marc E.. (2004). Les rues de Paris : « L’affaire Alexis Carrel ». médecine/sciences. 20. 707–709. 1 indexed citations

LeMaoult, Joël, Ilhem Messaoudi, John S. Manavalan, et al.. (2000). Age-Related Dysregulation in CD8 T Cell Homeostasis: Kinetics of a Diversity Loss. The Journal of Immunology. 165(5). 2367–2373. 76 indexed citations

LeMaoult, Joël, John S. Manavalan, Ruben Dyall, et al.. (1999). Cellular Basis of B Cell Clonal Populations in Old Mice. The Journal of Immunology. 162(11). 6384–6391. 32 indexed citations

LeMaoult, Joël, et al.. (1997). Clonal expansions of B lymphocytes in old mice. The Journal of Immunology. 159(8). 3866–3874. 45 indexed citations

Weksler, Marc E.. (1996). The Male Menopause: Restoring Vitality and Virility. BMJ. 313(7066). 1214.1–1214.1. 5 indexed citations

Zhao, Kesheng, et al.. (1995). Dysregulation of the humoral immune response in old mice. International Immunology. 7(6). 929–934. 38 indexed citations

10.

Chies, José Artur Bogo, et al.. (1994). V_H‐Gene Family Dominance in Ageing Mice. Scandinavian Journal of Immunology. 39(2). 184–188. 25 indexed citations

11.

Ehleiter, Desiree, A Ben-Yehuda, R. Schwab, et al.. (1993). Effect of age on the expressed B cell repertoire: role of B cell subsets. International Immunology. 5(9). 1035–1039. 43 indexed citations

12.

Weksler, Marc E., R. Schwab, François Huetz, Young Tai Kim, & António Coutinho. (1990). Cellular basis for the age-associated increase in autoimmune reactions. International Immunology. 2(4). 329–335. 25 indexed citations

13.

Russo, Carlo, et al.. (1989). Immunological studies of aging. Cellular Immunology. 119(1). 202–210. 96 indexed citations

14.

Weksler, Marc E., et al.. (1988). Immune Senescence Contributes to the Slow Growth of Tumors in Elderly Subjectsa. Annals of the New York Academy of Sciences. 521(1). 177–181. 6 indexed citations

15.

Fillit, Howard, Éva Kemény, Victoria N. Luine, Marc E. Weksler, & John B. Zabriskie. (1987). Antivascular Antibodies in the Sera of Patients With Senile Dementia of the Alzheimer's Type. Journal of Gerontology. 42(2). 180–184. 58 indexed citations

16.

Hariri, Robert, et al.. (1986). Aging and arteriosclerosis. I. Development of myointimal hyperplasia after endothelial injury.. The Journal of Experimental Medicine. 164(4). 1171–1178. 81 indexed citations

17.

Dutkowski, Regina, et al.. (1985). Increased chromosomal instability in lymphocytes from elderly humans. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis. 149(3). 505–512. 41 indexed citations

18.

Innes, J B, et al.. (1977). Immunological studies of Aging. III. Cytokinetic basis for the impaired response of lymphocytes from aged humans to plant lectins.. The Journal of Experimental Medicine. 145(5). 1176–1187. 120 indexed citations

19.

Szewczuk, Myron R., et al.. (1977). Differences in the mechanism of tolerance to dinitrophenylated bovine gamma globulin when induced in normal adult mice or in reconstituted irradiated mice: dependence of the mechanism of tolerance on the structural organization of the lymphoid system.. The Journal of Experimental Medicine. 145(4). 968–982. 9 indexed citations

20.

Weksler, Marc E.. (1976). Lymphocyte transformation induced by autologous cells. III. Lymphoblast-induced lymphocyte to stimulation does not correlate with EB viral antigen expression or immunity.. PubMed. 116(2). 310–4. 21 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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