Dorota Latek

1.4k total citations
32 papers, 879 citations indexed

About

Dorota Latek is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Dorota Latek has authored 32 papers receiving a total of 879 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 9 papers in Computational Theory and Mathematics. Recurrent topics in Dorota Latek's work include Receptor Mechanisms and Signaling (20 papers), Computational Drug Discovery Methods (9 papers) and Neuropeptides and Animal Physiology (8 papers). Dorota Latek is often cited by papers focused on Receptor Mechanisms and Signaling (20 papers), Computational Drug Discovery Methods (9 papers) and Neuropeptides and Animal Physiology (8 papers). Dorota Latek collaborates with scholars based in Poland, Germany and Belgium. Dorota Latek's co-authors include Sławomir Filipek, Bartosz Trzaskowski, Shuguang Yuan, Aleksander Dębiński, Umesh Ghoshdastider, Krzysztof Palczewski, Andrzej Koliński, Ingrid Langer, Teresa Carlomagno and Judyta Cielecka‐Piontek and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Dorota Latek

31 papers receiving 869 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dorota Latek Poland 14 675 356 123 88 69 32 879
Chunyou Mao China 16 699 1.0× 362 1.0× 75 0.6× 109 1.2× 40 0.6× 26 927
Ségolène Galandrin France 12 889 1.3× 518 1.5× 107 0.9× 97 1.1× 61 0.9× 13 1.1k
Gáspár Pándy‐Szekeres Hungary 8 809 1.2× 412 1.2× 162 1.3× 150 1.7× 39 0.6× 12 942
Wonjo Jang United States 8 610 0.9× 359 1.0× 58 0.5× 74 0.8× 37 0.5× 12 771
Youwen Zhuang China 12 661 1.0× 323 0.9× 58 0.5× 94 1.1× 129 1.9× 18 896
Maria Martí-Solano Spain 16 1.1k 1.7× 505 1.4× 86 0.7× 95 1.1× 58 0.8× 27 1.4k
H. Ongun Onaran Türkiye 17 916 1.4× 493 1.4× 93 0.8× 92 1.0× 45 0.7× 40 1.1k
Antoine Koehl United States 12 1.3k 1.9× 655 1.8× 91 0.7× 138 1.6× 82 1.2× 15 1.5k
Anke C. Schiedel Germany 21 713 1.1× 272 0.8× 115 0.9× 36 0.4× 51 0.7× 47 1.2k
Mireia Olivella Spain 16 629 0.9× 294 0.8× 53 0.4× 54 0.6× 31 0.4× 32 833

Countries citing papers authored by Dorota Latek

Since Specialization
Citations

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

Fields of papers citing papers by Dorota Latek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dorota Latek

This figure shows the co-authorship network connecting the top 25 collaborators of Dorota Latek. A scholar is included among the top collaborators of Dorota Latek 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 Dorota Latek. Dorota Latek 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.
Latek, Dorota, et al.. (2025). GPCRVS - AI-driven Decision Support System for GPCR Virtual Screening. International Journal of Molecular Sciences. 26(5). 2160–2160. 3 indexed citations
2.
Latek, Dorota, et al.. (2024). The two-sided impact of beta-adrenergic receptor ligands on inflammation. Current Opinion in Physiology. 41. 100779–100779. 2 indexed citations
3.
Gratio, Valérie, Luis Garcı́a, Loredana Saveanu, et al.. (2024). Pharmacodynamics of the orexin type 1 (OX1) receptor in colon cancer cell models: A two‐sided nature of antagonistic ligands resulting from partial dissociation of Gq. British Journal of Pharmacology. 182(7). 1528–1545. 2 indexed citations
4.
Sanmukh, Swapnil Ganesh, Nilton Barreto dos Santos, Flávia Karina Delella, et al.. (2023). Bacterial RNA virus MS2 exposure increases the expression of cancer progression genes in the LNCaP prostate cancer cell line. Oncology Letters. 25(2). 86–86. 6 indexed citations
5.
Merski, Matthew, et al.. (2023). Chemokine Receptors—Structure-Based Virtual Screening Assisted by Machine Learning. Pharmaceutics. 15(2). 516–516. 7 indexed citations
6.
Makal, Anna, et al.. (2022). Helix 8 in chemotactic receptors of the complement system. PLoS Computational Biology. 18(7). e1009994–e1009994.
7.
Langer, Ingrid & Dorota Latek. (2021). Drug Repositioning For Allosteric Modulation of VIP and PACAP Receptors. Frontiers in Endocrinology. 12. 711906–711906. 8 indexed citations
8.
Latek, Dorota, et al.. (2019). Drug-induced diabetes type 2: In silico study involving class B GPCRs. PLoS ONE. 14(1). e0208892–e0208892. 19 indexed citations
9.
Studzińska-Sroka, Elżbieta, Hanna Tomczak, Robert Kleszcz, et al.. (2019). Cladonia uncialis as a valuable raw material of biosynthetic compounds against clinical strains of bacteria and fungi. Acta Biochimica Polonica. 66(4). 597–603. 8 indexed citations
10.
11.
Miszta, Przemysław, et al.. (2017). Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists. Methods in molecular biology. 1705. 265–296. 3 indexed citations
12.
Latek, Dorota, et al.. (2013). Towards Improved Quality of GPCR Models by Usage of Multiple Templates and Profile-Profile Comparison. PLoS ONE. 8(2). e56742–e56742. 40 indexed citations
13.
Yuan, Shuguang, Umesh Ghoshdastider, Bartosz Trzaskowski, et al.. (2012). The Role of Water in Activation Mechanism of Human N-Formyl Peptide Receptor 1 (FPR1) Based on Molecular Dynamics Simulations. PLoS ONE. 7(11). e47114–e47114. 21 indexed citations
14.
Latek, Dorota, et al.. (2012). G protein-coupled receptors--recent advances.. Acta Biochimica Polonica. 59(4). 71 indexed citations
15.
Latek, Dorota, et al.. (2012). G protein-coupled receptors--recent advances.. PubMed. 59(4). 515–29. 67 indexed citations
16.
Latek, Dorota, Michał Koliński, Umesh Ghoshdastider, et al.. (2011). Modeling of ligand binding to G protein coupled receptors: cannabinoid CB1, CB2 and adrenergic β2AR. Journal of Molecular Modeling. 17(9). 2353–2366. 28 indexed citations
17.
Latek, Dorota & Andrzej Koliński. (2010). CABS‐NMR—De novo tool for rapid global fold determination from chemical shifts, residual dipolar couplings and sparse methyl‐methyl noes. Journal of Computational Chemistry. 32(3). 536–544. 12 indexed citations
18.
Latek, Dorota & Andrzej Koliński. (2008). Contact prediction in protein modeling: Scoring, folding and refinement of coarse-grained models. BMC Structural Biology. 8(1). 36–36. 11 indexed citations
19.
Latek, Dorota, Dariusz Ekonomiuk, & Andrzej Koliński. (2007). Protein structure prediction: Combining de novo modeling with sparse experimental data. Journal of Computational Chemistry. 28(10). 1668–1676. 16 indexed citations
20.
Koliński, Andrzej, Dominik Gront, Sebastian Kmiecik, Mateusz Kurciński, & Dorota Latek. (2006). Modeling protein structure, dynamics and thermodynamics with reduced representation of conformational space. 34. 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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