Michael A. Harvey

496 total citations
9 papers, 334 citations indexed

About

Michael A. Harvey is a scholar working on Immunology, Cognitive Neuroscience and Genetics. According to data from OpenAlex, Michael A. Harvey has authored 9 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Immunology, 3 papers in Cognitive Neuroscience and 3 papers in Genetics. Recurrent topics in Michael A. Harvey's work include Neural dynamics and brain function (3 papers), T-cell and B-cell Immunology (3 papers) and Immune Cell Function and Interaction (3 papers). Michael A. Harvey is often cited by papers focused on Neural dynamics and brain function (3 papers), T-cell and B-cell Immunology (3 papers) and Immune Cell Function and Interaction (3 papers). Michael A. Harvey collaborates with scholars based in United States, China and Spain. Michael A. Harvey's co-authors include Eli E. Sercarz, Luciano Adorini, Sliman J. Bensmaı̈a, Hannes P. Saal, Vanessa F. Descalzo, Albert Compte, María V. Sánchez-Vives, Ramón Reig, Alexander Miller and A. Miller and has published in prestigious journals such as Nature, The Journal of Experimental Medicine and Journal of Neuroscience.

In The Last Decade

Michael A. Harvey

9 papers receiving 305 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael A. Harvey United States	8	144	115	97	69	57	9	334
C. Travo France	11	69 0.5×	44 0.4×	208 2.1×	147 2.1×	46 0.8×	14	534
Jacqueline Morris United States	11	32 0.2×	23 0.2×	89 0.9×	213 3.1×	11 0.2×	13	362
Stefania Vescia Italy	10	360 2.5×	32 0.3×	162 1.7×	94 1.4×	9 0.2×	14	486
Genoveva Davidkova United States	10	27 0.2×	33 0.3×	108 1.1×	247 3.6×	11 0.2×	14	401
S. MacRae Canada	10	14 0.1×	231 2.0×	16 0.2×	59 0.9×	35 0.6×	32	402
Miyo Kakizaki Japan	9	126 0.9×	77 0.7×	50 0.5×	83 1.2×	15 0.3×	14	330
Isaac Shamie United States	9	90 0.6×	9 0.1×	46 0.5×	193 2.8×	26 0.5×	12	310
Teppei Ebina Japan	10	150 1.0×	8 0.1×	156 1.6×	212 3.1×	32 0.6×	18	438
Sherry Lin United States	13	43 0.3×	185 1.6×	47 0.5×	322 4.7×	32 0.6×	22	605

Countries citing papers authored by Michael A. Harvey

Since Specialization

Citations

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

Fields of papers citing papers by Michael A. Harvey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael A. Harvey

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Harvey. A scholar is included among the top collaborators of Michael A. Harvey 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 Michael A. Harvey. Michael A. Harvey 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

Yao, Gang, Chong Luo, Michael A. Harvey, et al.. (2015). Disruption of polycystin-L causes hippocampal and thalamocortical hyperexcitability. Human Molecular Genetics. 25(3). 448–458. 23 indexed citations

Saal, Hannes P., Michael A. Harvey, & Sliman J. Bensmaı̈a. (2015). Rate and timing of cortical responses driven by separate sensory channels. eLife. 4. e10450–e10450. 48 indexed citations

Compte, Albert, et al.. (2008). Spontaneous High-Frequency (10–80 Hz) Oscillations during Up States in the Cerebral CortexIn Vitro. Journal of Neuroscience. 28(51). 13828–13844. 91 indexed citations

Harvey, Michael A.. (2001). Cortical barrel field ablation and unconditioned whisking kinematics. Somatosensory & Motor Research. 18(3). 223–227. 24 indexed citations

Sercarz, Eli E., Barbara A. Araneo, Christopher D. Benjamin, et al.. (1983). The Design of Regulatory Circuitry: Predominant Idiotypy and the Idea of Regulatory Parsimony^a. Annals of the New York Academy of Sciences. 418(1). 198–205. 6 indexed citations

Adorini, Luciano, et al.. (1980). Differential major histocompatibility complex-related activation of idiotypic suppressor T cells. Suppressor T cells cross-reactive to two distantly related lysozymes are not induced by one of them.. The Journal of Experimental Medicine. 152(3). 521–531. 8 indexed citations

Benjamin, Christopher D., A. Miller, Eli E. Sercarz, & Michael A. Harvey. (1980). A predominant idiotype on anti-hen egg white lysozyme antibodies from diverse mouses strains.. The Journal of Immunology. 125(3). 1017–1025. 22 indexed citations

Adorini, Luciano, Michael A. Harvey, & Eli E. Sercarz. (1979). The fine specificity of regulatory T cells IV. Idiotypic complementarity and antigen‐bridging interactions in the anti‐lysozyme response. European Journal of Immunology. 9(11). 906–909. 61 indexed citations

Harvey, Michael A., Luciano Adorini, Alexander Miller, & Eli E. Sercarz. (1979). Lysozyme-induced T-suppressor cells and antibodies have a predominant idiotype. Nature. 281(5732). 594–596. 51 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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