Gennady Poda

1.4k total citations
33 papers, 741 citations indexed

About

Gennady Poda is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Gennady Poda has authored 33 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 9 papers in Computational Theory and Mathematics and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Gennady Poda's work include Computational Drug Discovery Methods (9 papers), Receptor Mechanisms and Signaling (5 papers) and Neuropeptides and Animal Physiology (5 papers). Gennady Poda is often cited by papers focused on Computational Drug Discovery Methods (9 papers), Receptor Mechanisms and Signaling (5 papers) and Neuropeptides and Animal Physiology (5 papers). Gennady Poda collaborates with scholars based in Canada, Ukraine and United States. Gennady Poda's co-authors include Andriy I. Vovk, Vsevolod Yu. Tanchuk, Igor V. Tetko, Bernard Maigret, Lionel Moulédous, Christopher M. Topham, Jean‐Claude Meunier, Andrei K. Yudin, Shinya Adachi and Gilbert G. Privé and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Molecular Biology and Journal of Medicinal Chemistry.

In The Last Decade

Gennady Poda

29 papers receiving 717 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gennady Poda Canada 13 476 156 146 105 59 33 741
Xiangrui Jiang China 16 475 1.0× 242 1.6× 182 1.2× 49 0.5× 74 1.3× 79 1.0k
Mingyun Shen China 14 687 1.4× 166 1.1× 299 2.0× 43 0.4× 110 1.9× 15 1.0k
Jing Su China 15 543 1.1× 65 0.4× 42 0.3× 57 0.5× 78 1.3× 47 766
Soma Samanta India 16 281 0.6× 158 1.0× 171 1.2× 28 0.3× 68 1.2× 35 658
Armin Madadkar‐Sobhani Iran 17 440 0.9× 309 2.0× 172 1.2× 18 0.2× 98 1.7× 34 813
Chun Hu China 16 462 1.0× 361 2.3× 87 0.6× 49 0.5× 86 1.5× 87 990
Robert S. Rush United States 15 326 0.7× 83 0.5× 160 1.1× 41 0.4× 49 0.8× 22 731
Andreas Evers Germany 21 1.1k 2.4× 170 1.1× 528 3.6× 280 2.7× 121 2.1× 55 1.6k
Varnavas D. Mouchlis United States 20 654 1.4× 120 0.8× 331 2.3× 33 0.3× 42 0.7× 36 1.1k
Jinhong Feng China 18 471 1.0× 239 1.5× 43 0.3× 29 0.3× 152 2.6× 52 818

Countries citing papers authored by Gennady Poda

Since Specialization
Citations

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

Fields of papers citing papers by Gennady Poda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gennady Poda

This figure shows the co-authorship network connecting the top 25 collaborators of Gennady Poda. A scholar is included among the top collaborators of Gennady Poda 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 Gennady Poda. Gennady Poda 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.
Kotelnikov, Sergei, Konstantin I. Popov, Mikhail Ignatov, et al.. (2023). Accurate ligand–protein docking in CASP15 using the ClusPro LigTBM server. Proteins Structure Function and Bioinformatics. 91(12). 1822–1828. 3 indexed citations
2.
Liu, Jiabao, Çiğdem Şahin, Lilia Magomedova, et al.. (2022). The omega-3 hydroxy fatty acid 7( S )-HDHA is a high-affinity PPARα ligand that regulates brain neuronal morphology. Science Signaling. 15(741). eabo1857–eabo1857. 25 indexed citations
3.
Şahin, Çiğdem, Lilia Magomedova, Jiabao Liu, et al.. (2022). Phenolic Lipids Derived from Cashew Nut Shell Liquid to Treat Metabolic Diseases. Journal of Medicinal Chemistry. 65(3). 1961–1978. 17 indexed citations
4.
Uehling, David, Babu Joseph, Kim Chan Chung, et al.. (2021). Design, Synthesis, and Characterization of 4-Aminoquinazolines as Potent Inhibitors of the G Protein-Coupled Receptor Kinase 6 (GRK6) for the Treatment of Multiple Myeloma. Journal of Medicinal Chemistry. 64(15). 11129–11147. 16 indexed citations
5.
Kovalishyn, Vasyl, Diana Hodyna, Ivan Semenyuta, et al.. (2019). Hybrid Design of Isonicotinic Acid Hydrazide Derivatives: Machine Learning Studies, Synthesis and Biological Evaluation of their Antituberculosis Activity. Current Drug Discovery Technologies. 17(3). 365–375. 4 indexed citations
6.
Christott, Thomas, James M. Bennett, Carmen Coxon, et al.. (2018). Discovery of a Selective Inhibitor for the YEATS Domains of ENL/AF9. SLAS DISCOVERY. 24(2). 133–141. 40 indexed citations
7.
Poda, Gennady, et al.. (2017). Establishment of Some Biochemical Parameters and their Variation in West African Donkeysâ Breed. 11(3). 1 indexed citations
8.
Getlik, Matthäus, David Smil, Carlos Zepeda‐Velázquez, et al.. (2016). Structure-Based Optimization of a Small Molecule Antagonist of the Interaction Between WD Repeat-Containing Protein 5 (WDR5) and Mixed-Lineage Leukemia 1 (MLL1). Journal of Medicinal Chemistry. 59(6). 2478–2496. 67 indexed citations
9.
Huang, Jingjing, et al.. (2016). Structure of Human Acid Sphingomyelinase Reveals the Role of the Saposin Domain in Activating Substrate Hydrolysis. Journal of Molecular Biology. 428(15). 3026–3042. 43 indexed citations
10.
Tanchuk, Vsevolod Yu., et al.. (2015). A New Scoring Function for Molecular Docking Based on AutoDock and AutoDock Vina. Current Drug Discovery Technologies. 12(3). 170–178. 10 indexed citations
11.
Adachi, Shinya, Sean K. Liew, Alan J. Lough, et al.. (2015). Condensation-Driven Assembly of Boron-Containing Bis(Heteroaryl) Motifs Using a Linchpin Approach. Organic Letters. 17(22). 5594–5597. 72 indexed citations
12.
McFadyen, Iain J., et al.. (2002). 4 Molecular Modeling of Opioid Receptor-Ligand Complexes. Progress in medicinal chemistry. 107–135. 10 indexed citations
13.
Bourdonnec, Bertrand Le, Rachid El Kouhen, Gennady Poda, et al.. (2001). Covalently Induced Activation of the δ Opioid Receptor by a Fluorogenic Affinity Label, 7‘-(Phthalaldehydecarboxamido)naltrindole (PNTI). Journal of Medicinal Chemistry. 44(7). 1017–1020. 10 indexed citations
14.
Topham, Christopher M., Lionel Moulédous, Gennady Poda, Bernard Maigret, & Jean‐Claude Meunier. (1998). Molecular modelling of the ORL1 receptor and its complex with nociceptin. Protein Engineering Design and Selection. 11(12). 1163–1179. 71 indexed citations
15.
16.
Tetko, Igor V., et al.. (1994). HIV-1 Reverse Transcriptase Inhibitor Design Using Artificial Neural Networks. Journal of Medicinal Chemistry. 37(16). 2520–2526. 40 indexed citations
17.
Tetko, Igor V., et al.. (1993). Applications of neural networks in structure-activity relationships of a small number of molecules. Journal of Medicinal Chemistry. 36(7). 811–814. 68 indexed citations
18.
Massa, S., et al.. (1989). A bacteriological survey of retail ice cream. Food Microbiology. 6(3). 129–134. 8 indexed citations
19.
Massa, S., et al.. (1989). Coliform detection from river waters: Comparison between MPN and MF techniques. Water Air & Soil Pollution. 43(1-2). 135–145. 5 indexed citations
20.
Trovatelli, L.D., et al.. (1988). Microbiological quality of fresh pasta dumplings sold in Bologna and the surrounding district. International Journal of Food Microbiology. 7(1). 19–24. 9 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Xiangrui Jiang Breakdown of academic impact, for papers by Mingyun Shen Breakdown of academic impact, for papers by Jing Su Breakdown of academic impact, for papers by Soma Samanta Breakdown of academic impact, for papers by Armin Madadkar‐Sobhani Breakdown of academic impact, for papers by Chun Hu Breakdown of academic impact, for papers by Robert S. Rush Breakdown of academic impact, for papers by Andreas Evers Breakdown of academic impact, for papers by Varnavas D. Mouchlis Breakdown of academic impact, for papers by Jinhong Feng
Rankless by CCL
2026