M. Geffard

13.1k total citations
281 papers, 10.4k citations indexed

About

M. Geffard is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Physiology. According to data from OpenAlex, M. Geffard has authored 281 papers receiving a total of 10.4k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Cellular and Molecular Neuroscience, 87 papers in Molecular Biology and 40 papers in Physiology. Recurrent topics in M. Geffard's work include Neuroscience and Neuropharmacology Research (69 papers), Receptor Mechanisms and Signaling (35 papers) and Neurotransmitter Receptor Influence on Behavior (32 papers). M. Geffard is often cited by papers focused on Neuroscience and Neuropharmacology Research (69 papers), Receptor Mechanisms and Signaling (35 papers) and Neurotransmitter Receptor Influence on Behavior (32 papers). M. Geffard collaborates with scholars based in France, Spain and Thailand. M. Geffard's co-authors include Ruud M. Buijs, Philippe Séguéla, A. Calas, Michel Le Moal, Michaël Maes, Alain Privat, N. Rajaofetra, N. Mons, Kunio Kitahama and Ikuko Nagatsu 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

M. Geffard

280 papers receiving 10.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
M. Geffard 5.6k 2.9k 1.4k 1.3k 1.3k 281 10.4k
Efrain C. Azmitia 7.3k 1.3× 3.7k 1.3× 1.1k 0.8× 1.4k 1.1× 2.8k 2.2× 186 12.4k
Christoph Kellendonk 4.1k 0.7× 3.8k 1.3× 1.5k 1.1× 1.8k 1.4× 2.4k 1.9× 93 11.2k
David Weinshenker 4.4k 0.8× 2.6k 0.9× 1.7k 1.2× 702 0.5× 1.6k 1.2× 171 8.3k
David L. Felten 3.1k 0.6× 2.1k 0.7× 1.2k 0.9× 1.1k 0.9× 562 0.4× 156 9.1k
Jay A. Gingrich 5.2k 0.9× 4.4k 1.5× 860 0.6× 598 0.5× 1.2k 1.0× 90 10.5k
Laurence H. Tecott 3.9k 0.7× 3.4k 1.2× 1.9k 1.4× 2.2k 1.7× 1.1k 0.9× 78 9.8k
George R. Siggins 6.8k 1.2× 3.8k 1.3× 1.2k 0.9× 946 0.7× 1.9k 1.5× 127 9.6k
Mohamed Jaber 8.0k 1.4× 5.0k 1.7× 934 0.7× 638 0.5× 2.0k 1.5× 106 12.1k
Baljit S. Khakh 7.4k 1.3× 5.4k 1.9× 2.0k 1.4× 2.3k 1.8× 1.8k 1.4× 130 16.1k
Jean M. Lauder 5.3k 0.9× 3.9k 1.3× 706 0.5× 979 0.8× 1.2k 1.0× 150 11.5k

Countries citing papers authored by M. Geffard

Since Specialization
Citations

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

Fields of papers citing papers by M. Geffard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Geffard. 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 M. Geffard. The network helps show where M. Geffard may publish in the future.

Co-authorship network of co-authors of M. Geffard

This figure shows the co-authorship network connecting the top 25 collaborators of M. Geffard. A scholar is included among the top collaborators of M. Geffard 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 M. Geffard. M. Geffard 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
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Roomruangwong, Chutima, André F. Carvalho, M. Geffard, & Michaël Maes. (2019). The menstrual cycle may not be limited to the endometrium but also may impact gut permeability. Acta Neuropsychiatrica. 31(6). 294–304. 19 indexed citations
3.
Maes, Michaël, Aristo Vojdani, M. Geffard, et al.. (2019). Schizophrenia phenomenology comprises a bifactorial general severity and a single-group factor, which are differently associated with neurotoxic immune and immune-regulatory pathways. BioMolecular Concepts. 10(1). 209–225. 22 indexed citations
4.
Kanchanatawan, Buranee, Sira Sriswasdi, Supaksorn Thika, et al.. (2018). Towards a new classification of stable phase schizophrenia into major and simple neuro‐cognitive psychosis: Results of unsupervised machine learning analysis. Journal of Evaluation in Clinical Practice. 24(4). 879–891. 29 indexed citations
6.
Kanchanatawan, Buranee, Sira Sriswasdi, Supaksorn Thika, et al.. (2018). Deficit schizophrenia is a discrete diagnostic category defined by neuro-immune and neurocognitive features: results of supervised machine learning. Metabolic Brain Disease. 33(4). 1053–1067. 36 indexed citations
8.
Roomruangwong, Chutima, Décio Sabbatini Barbosa, Andressa Keiko Matsumoto, et al.. (2017). Natural regulatory IgM‐mediated autoimmune responses directed against malondialdehyde regulate oxidative and nitrosative pathways and coupled with IgM responses to nitroso adducts attenuate depressive and physiosomatic symptoms at the end of term pregnancy. Psychiatry and Clinical Neurosciences. 72(2). 116–130. 14 indexed citations
10.
Maes, Michaël, Ivana Mihaylova, Marta Kubera, et al.. (2012). IgM-mediated autoimmune responses directed against anchorage epitopes are greater in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) than in major depression. Metabolic Brain Disease. 27(4). 415–423. 42 indexed citations
11.
Mangas, A., et al.. (2006). Riboflavin-like inmunoreactive fibers in the monkey brain. Anatomy and Embryology. 211(4). 267–272. 11 indexed citations
12.
Lorch, Scott A., Andrew J. Gow, Andrew L. Salzman, et al.. (2000). Immunohistochemical Localization of Protein 3-Nitrotyrosine and S-nitrosocysteine in a Murine Model of Inhaled Nitric Oxide Therapy. Pediatric Research. 47(6). 798–805. 36 indexed citations
13.
14.
Loirand, Gervaise, et al.. (1992). Autoanti-phosphatidylinositide antibodies specifically inhibit noradrenaline effects on Ca2+ and Cl- channels in rat portal vein myocytes.. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
15.
Marlier, L., F. Sandillon, P. Poulat, et al.. (1991). Serotonergic innervation of the dorsal horn of rat spinal cord: light and electron microscopic immunocytochemical study. Journal of Neurocytology. 20(4). 310–322. 101 indexed citations
16.
Manier, M., Claude Feuerstein, Patrick Mouchet, et al.. (1990). Evidence for the existence of L-dopa- and dopamine-immunoreactive nerve cell bodies in the caudal part of the dorsal motor nucleus of the vagus nerve.. PubMed. 3(3). 193–205. 25 indexed citations
17.
Kitahama, Kunio, M. Geffard, Hitoshi Okamura, et al.. (1990). Dopamine- and DOPA-immunoreactive neurons in the cat forebrain with reference to tyrosine hydroxylase-immunohistochemistry. Brain Research. 518(1-2). 83–94. 70 indexed citations
18.
Pituello, Fabienne, Paulette Kan, M. Geffard, & A.M. Duprat. (1989). Initial GABAergic expression in embryonic amphibian neuroblasts after neural induction. The International Journal of Developmental Biology. 33(4). 445–453. 9 indexed citations
19.
Geffard, M., et al.. (1989). Monoclonal Anti‐Conjugated Acetylcholine Antibody and Immunohistochemical Applications in Rat Nervous System. Journal of Neurochemistry. 53(2). 383–391. 13 indexed citations
20.
Eybalin, Michel, et al.. (1988). Immunoelectron microscopy identifies several types of GABA-containing efferent synapses in the guinea-pig organ of Corti. Neuroscience. 24(1). 29–38. 79 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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