Connie Sánchez

10.7k total citations · 1 hit paper
210 papers, 8.6k citations indexed

About

Connie Sánchez is a scholar working on Cellular and Molecular Neuroscience, Pharmacology and Molecular Biology. According to data from OpenAlex, Connie Sánchez has authored 210 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Cellular and Molecular Neuroscience, 83 papers in Pharmacology and 51 papers in Molecular Biology. Recurrent topics in Connie Sánchez's work include Treatment of Major Depression (81 papers), Neurotransmitter Receptor Influence on Behavior (78 papers) and Neuroscience and Neuropharmacology Research (62 papers). Connie Sánchez is often cited by papers focused on Treatment of Major Depression (81 papers), Neurotransmitter Receptor Influence on Behavior (78 papers) and Neuroscience and Neuropharmacology Research (62 papers). Connie Sánchez collaborates with scholars based in Denmark, United States and France. Connie Sánchez's co-authors include Alan L. Pehrson, John Hyttel, Eddi Meier, Francesc Artigas, Nasser Haddjeri, Karen E. Asin, Elena Dale, Jørn Arnt, Ove Wiborg and Maria Gulinello and has published in prestigious journals such as SHILAP Revista de lepidopterología, Biological Psychiatry and Brain Research.

In The Last Decade

Connie Sánchez

208 papers receiving 8.3k citations

Hit Papers

Vortioxetine, a novel ant... 2014 2026 2018 2022 2014 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Connie Sánchez 3.8k 2.8k 2.0k 1.7k 1.4k 210 8.6k
Jeffrey H. Meyer 3.5k 0.9× 2.1k 0.7× 1.6k 0.8× 2.4k 1.4× 1.8k 1.3× 153 9.9k
Michel Bourin 4.8k 1.3× 1.7k 0.6× 2.7k 1.3× 1.5k 0.9× 1.2k 0.9× 307 10.9k
Gabriella Gobbi 3.3k 0.9× 2.6k 0.9× 1.4k 0.7× 911 0.5× 1.3k 1.0× 138 7.7k
Piotr Popik 3.8k 1.0× 1.6k 0.6× 2.3k 1.1× 1.3k 0.8× 1.1k 0.8× 176 7.5k
Alan Frazer 4.8k 1.3× 1.7k 0.6× 3.0k 1.5× 1.2k 0.7× 1.3k 1.0× 211 10.3k
Mike Briley 4.7k 1.3× 1.9k 0.7× 2.7k 1.3× 1.1k 0.6× 1.5k 1.1× 121 11.0k
Gregers Wegener 2.6k 0.7× 1.6k 0.6× 1.9k 0.9× 2.3k 1.4× 835 0.6× 252 8.1k
Maurizio Popoli 3.3k 0.9× 1.4k 0.5× 1.7k 0.8× 2.6k 1.6× 1.1k 0.8× 149 7.6k
Alain M. Gardier 4.8k 1.3× 1.7k 0.6× 3.3k 1.6× 1.8k 1.1× 1.0k 0.8× 156 8.7k
Alexander Neumeister 2.3k 0.6× 1.6k 0.6× 835 0.4× 1.2k 0.7× 2.2k 1.6× 155 7.6k

Countries citing papers authored by Connie Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Connie Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Connie Sánchez

This figure shows the co-authorship network connecting the top 25 collaborators of Connie Sánchez. A scholar is included among the top collaborators of Connie Sánchez 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 Connie Sánchez. Connie Sánchez 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.
2.
Sánchez, Connie, et al.. (2023). Characterization of pain-, anxiety-, and cognition-related behaviors in the complete Freund's adjuvant model of chronic inflammatory pain in Wistar–Kyoto rats. SHILAP Revista de lepidopterología. 4. 1131069–1131069. 8 indexed citations
3.
Landau, Anne M., et al.. (2023). Changes in hypothalamic mu-opioid receptor expression following acute olanzapine treatment in female rats: Implications for feeding behavior. Journal of Chemical Neuroanatomy. 132. 102324–102324. 3 indexed citations
4.
Landau, Anne M., et al.. (2022). Spatial quantification of single cell mRNA and ligand binding of the kappa opioid receptor in the rat hypothalamus. Journal of Chemical Neuroanatomy. 127. 102205–102205. 3 indexed citations
5.
Elfving, Betina, et al.. (2022). Single dose S-ketamine rescues transcriptional dysregulation of Mtor and Nrp2 in the prefrontal cortex of FSL rats 1 hour but not 14 days post dosing. European Neuropsychopharmacology. 65. 56–67. 3 indexed citations
6.
Wegener, Gregers, et al.. (2020). Opioid system modulation of cognitive affective bias: implications for the treatment of mood disorders. Behavioural Pharmacology. 31(2&3). 122–135. 11 indexed citations
7.
Puryear, Corey B., Julie M. Brooks, Laura A. Tan, et al.. (2019). Opioid receptor modulation of neural circuits in depression: What can be learned from preclinical data?. Neuroscience & Biobehavioral Reviews. 108. 658–678. 35 indexed citations
9.
Jardin, Kristian Gaarn du, Heidi Kaastrup Müller, Connie Sánchez, Gregers Wegener, & Betina Elfving. (2016). Gene expression related to serotonergic and glutamatergic neurotransmission is altered in the flinders sensitive line rat model of depression: Effect of ketamine. Synapse. 71(1). 37–45. 15 indexed citations
10.
David, Denis J., Laurent Tritschler, Jean‐Philippe Guilloux, et al.. (2016). Propriétés pharmacologiques de la vortioxetine et leurs conséquences pré-cliniques. L Encéphale. 42(1). 1S12–1S23. 5 indexed citations
11.
Felice, Daniela, Olivia F. O’Leary, John F. Cryan, et al.. (2015). When ageing meets the blues: Are current antidepressants effective in depressed aged patients?. Neuroscience & Biobehavioral Reviews. 55. 478–497. 17 indexed citations
12.
Dale, Elena, Alan L. Pehrson, Yan Li, et al.. (2015). Effects of serotonin in the hippocampus: how SSRIs and multimodal antidepressants might regulate pyramidal cell function. CNS Spectrums. 21(2). 143–161. 118 indexed citations
13.
Dale, Elena, Benny Bang‐Andersen, & Connie Sánchez. (2015). Emerging mechanisms and treatments for depression beyond SSRIs and SNRIs. Biochemical Pharmacology. 95(2). 81–97. 174 indexed citations
14.
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Sánchez, Connie, Karen E. Asin, & Francesc Artigas. (2014). Vortioxetine, a novel antidepressant with multimodal activity: Review of preclinical and clinical data. Pharmacology & Therapeutics. 145. 43–57. 400 indexed citations breakdown →
16.
Sánchez, Connie, Elin Heldbo Reines, & Stuart Montgomery. (2014). A comparative review of escitalopram, paroxetine, and sertraline. International Clinical Psychopharmacology. 29(4). 185–196. 190 indexed citations
17.
Artigas, Francesc, Maurizio S. Riga, Pau Celada, & Connie Sánchez. (2013). Poster Session I. Neuropsychopharmacology. 38(S2). S108–S272. 2 indexed citations
18.
Jacquot, C., Denis J. David, Alain M. Gardier, & Connie Sánchez. (2007). Escitalopram et Citalopram : le rôle inattendu de l’énantiomère R. L Encéphale. 33(2). 179–187. 16 indexed citations
19.
Sánchez, Connie. (2006). The Pharmacology of Citalopram Enantiomers: The Antagonism by R‐Citalopram on the Effect of S‐Citalopram*. Basic & Clinical Pharmacology & Toxicology. 99(2). 91–95. 97 indexed citations
20.
Mitchell, Paul J., S. Hogg, & Connie Sánchez. (2004). Agonistic behaviour of resident rats after acute and chronic treatment with S(+)- and R(-)-citalopram. The International Journal of Neuropsychopharmacology. 7. 1 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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