Larysa Teplytska

832 total citations
19 papers, 671 citations indexed

About

Larysa Teplytska is a scholar working on Biological Psychiatry, Molecular Biology and Physiology. According to data from OpenAlex, Larysa Teplytska has authored 19 papers receiving a total of 671 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Biological Psychiatry, 8 papers in Molecular Biology and 5 papers in Physiology. Recurrent topics in Larysa Teplytska's work include Tryptophan and brain disorders (10 papers), Advanced Proteomics Techniques and Applications (5 papers) and Stress Responses and Cortisol (4 papers). Larysa Teplytska is often cited by papers focused on Tryptophan and brain disorders (10 papers), Advanced Proteomics Techniques and Applications (5 papers) and Stress Responses and Cortisol (4 papers). Larysa Teplytska collaborates with scholars based in Germany, United States and Greece. Larysa Teplytska's co-authors include Christoph W. Turck, Michaela D. Filiou, Giuseppina Maccarrone, Markus Nußbaumer, Rainer Landgraf, Stefan Reckow, John M. Asara, Claudia Ditzen, Alexander Yassouridis and Mirjam Bunck and has published in prestigious journals such as Scientific Reports, Biological Psychiatry and The FASEB Journal.

In The Last Decade

Larysa Teplytska

19 papers receiving 657 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Larysa Teplytska Germany 14 307 305 175 132 129 19 671
Natacha Vanattou‐Saïfoudine United Kingdom 9 192 0.6× 149 0.5× 83 0.5× 61 0.5× 123 1.0× 12 441
Jelena Zlatković Serbia 14 200 0.7× 465 1.5× 255 1.5× 304 2.3× 191 1.5× 18 1.1k
Caroline Madeira Brazil 13 274 0.9× 337 1.1× 28 0.2× 199 1.5× 311 2.4× 16 924
Marta Marszałek‐Grabska Poland 11 113 0.4× 175 0.6× 93 0.5× 107 0.8× 213 1.7× 34 580
Anita Kulak Switzerland 6 228 0.7× 130 0.4× 105 0.6× 49 0.4× 198 1.5× 9 507
Charles Vargas-Lopes Brazil 10 260 0.8× 299 1.0× 25 0.1× 186 1.4× 277 2.1× 10 750
Carol J. Grossman United Kingdom 7 241 0.8× 475 1.6× 133 0.8× 123 0.9× 585 4.5× 8 1.0k
J.H. Connick United Kingdom 13 235 0.8× 289 0.9× 134 0.8× 81 0.6× 444 3.4× 27 764
Vanessa Athaíde Garcia Brazil 14 48 0.2× 198 0.6× 93 0.5× 107 0.8× 304 2.4× 18 765

Countries citing papers authored by Larysa Teplytska

Since Specialization
Citations

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

Fields of papers citing papers by Larysa Teplytska

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Larysa Teplytska

This figure shows the co-authorship network connecting the top 25 collaborators of Larysa Teplytska. A scholar is included among the top collaborators of Larysa Teplytska 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 Larysa Teplytska. Larysa Teplytska is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Filiou, Michaela D., et al.. (2022). Multi-Omics Analysis Reveals Myelin, Presynaptic and Nicotinate Alterations in the Hippocampus of G72/G30 Transgenic Mice. Journal of Personalized Medicine. 12(2). 244–244. 5 indexed citations
2.
Filiou, Michaela D., Markus Nußbaumer, Larysa Teplytska, & Christoph W. Turck. (2021). Behavioral and Metabolome Differences between C57BL/6 and DBA/2 Mouse Strains: Implications for Their Use as Models for Depression- and Anxiety-Like Phenotypes. Metabolites. 11(2). 128–128. 13 indexed citations
3.
Weckmann, Katja, Michael J. Deery, Julie A. Howard, et al.. (2017). Ketamine’s antidepressant effect is mediated by energy metabolism and antioxidant defense system. Scientific Reports. 7(1). 15788–15788. 70 indexed citations
4.
Teplytska, Larysa, João Vaz‐Silva, Chrysoula Dioli, et al.. (2016). Tau Deletion Prevents Stress-Induced Dendritic Atrophy in Prefrontal Cortex: Role of Synaptic Mitochondria. Cerebral Cortex. 27(4). bhw057–bhw057. 57 indexed citations
5.
Turck, Christoph W., Christian Webhofer, Markus Nußbaumer, et al.. (2016). Stable isotope metabolic labeling suggests differential turnover of the DPYSL protein family. PROTEOMICS - CLINICAL APPLICATIONS. 10(12). 1269–1272. 7 indexed citations
6.
Nußbaumer, Markus, John M. Asara, Larysa Teplytska, et al.. (2015). Selective Mitochondrial Targeting Exerts Anxiolytic Effects In Vivo. Neuropsychopharmacology. 41(7). 1751–1758. 39 indexed citations
7.
Filiou, Michaela D., John M. Asara, Markus Nußbaumer, et al.. (2014). Behavioral extremes of trait anxiety in mice are characterized by distinct metabolic profiles. Journal of Psychiatric Research. 58. 115–122. 40 indexed citations
8.
Filiou, Michaela D., Christian Webhofer, Philipp Gormanns, et al.. (2012). The 15N isotope effect as a means for correlating phenotypic alterations and affected pathways in a trait anxiety mouse model. PROTEOMICS. 12(15-16). 2421–2427. 10 indexed citations
9.
Filiou, Michaela D., Larysa Teplytska, David M. Otte, Andreas Zimmer, & Christoph W. Turck. (2012). Myelination and oxidative stress alterations in the cerebellum of the G72/G30 transgenic schizophrenia mouse model. Journal of Psychiatric Research. 46(10). 1359–1365. 33 indexed citations
10.
Filiou, Michaela D., et al.. (2012). The 15 N isotope effect in Escherichia coli : A neutron can make the difference. PROTEOMICS. 12(21). 3121–3128. 22 indexed citations
11.
Ditzen, Claudia, Ning Tang, Larysa Teplytska, et al.. (2011). Cerebrospinal Fluid Biomarkers for Major Depression Confirm Relevance of Associated Pathophysiology. Neuropsychopharmacology. 37(4). 1013–1025. 77 indexed citations
12.
Filiou, Michaela D., Yaoyang Zhang, Larysa Teplytska, et al.. (2011). Proteomics and Metabolomics Analysis of a Trait Anxiety Mouse Model Reveals Divergent Mitochondrial Pathways. Biological Psychiatry. 70(11). 1074–1082. 124 indexed citations
13.
Filiou, Michaela D., Birgit Bisle, Stefan Reckow, et al.. (2010). Profiling of mouse synaptosome proteome and phosphoproteome by IEF. Electrophoresis. 31(8). 1294–1301. 46 indexed citations
14.
Filiou, Michaela D., Yaoyang Zhang, Larysa Teplytska, et al.. (2010). Biomarker discovery by stable isotope labeling and quantitative proteomics. The FASEB Journal. 24(S1). 1 indexed citations
15.
Ditzen, Claudia, Ludwig Czibere, Mariya Gonik, et al.. (2009). Proteomic-based genotyping in a mouse model of trait anxiety exposes disease-relevant pathways. Molecular Psychiatry. 15(7). 702–711. 29 indexed citations
16.
Ditzen, Claudia, Ludwig Czibere, Mariya Gonik, et al.. (2009). Proteomic genotyping in a mouse model of trait anxiety exposes disease relevant pathways. Pharmacopsychiatry. 42(5). 1 indexed citations
17.
Maccarrone, Giuseppina, et al.. (2006). Phosphopeptide enrichment by IEF. Electrophoresis. 27(22). 4585–4595. 18 indexed citations
18.
Ditzen, Claudia, Melanie Keßler, Mirjam Bunck, et al.. (2006). Protein Biomarkers in a Mouse Model of Extremes in Trait Anxiety. Molecular & Cellular Proteomics. 5(10). 1914–1920. 64 indexed citations
19.
Turck, Christoph W., Giuseppina Maccarrone, Claudia Ditzen, et al.. (2005). The quest for brain disorder biomarkers. The Journal of Medical Investigation. 52(Supplement). 231–235. 15 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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