Justas Dapkūnas

1.1k total citations
22 papers, 445 citations indexed

About

Justas Dapkūnas is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Justas Dapkūnas has authored 22 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 9 papers in Materials Chemistry and 5 papers in Computational Theory and Mathematics. Recurrent topics in Justas Dapkūnas's work include Protein Structure and Dynamics (13 papers), Enzyme Structure and Function (9 papers) and Computational Drug Discovery Methods (5 papers). Justas Dapkūnas is often cited by papers focused on Protein Structure and Dynamics (13 papers), Enzyme Structure and Function (9 papers) and Computational Drug Discovery Methods (5 papers). Justas Dapkūnas collaborates with scholars based in Lithuania, Spain and France. Justas Dapkūnas's co-authors include Iain H. Moal, Juan Fernández‐Recio, Brian Jiménez‐García, Česlovas Venclovas, Kliment Olechnovič, Pranas Japertas, Remigijus Didžiapetris, Mindaugas Margelevičius, Albertas Timinskas and Aurelija Žvirblienė and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Scientific Reports.

In The Last Decade

Justas Dapkūnas

21 papers receiving 441 citations

Peers

Justas Dapkūnas

CTM

RNMI

PHARM

Melissa Landon United States

Siqi Liang United States

Anna C. Salzberg United States

Brandon S. Zerbe United States

Jesse Woo United States

Maria G. Carr United Kingdom

Joerg Bomke Germany

Martin Weisel Germany

António J. Preto Portugal

Gerdien E. de Kloe Netherlands

Melissa Landon United States

Justas Dapkūnas

591 ×1.7

303 ×2.2

CTM

135 ×1.5

63 ×1.2

RNMI

21 ×0.5

PHARM

Citations per year, relative to Justas Dapkūnas Justas Dapkūnas (= 1×) peers Melissa Landon

Countries citing papers authored by Justas Dapkūnas

Since Specialization

Citations

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

Fields of papers citing papers by Justas Dapkūnas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Justas Dapkūnas

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Dapkūnas, Justas & Česlovas Venclovas. (2025). Databases and web-based tools for studying structures of protein-nucleic acid complexes. Current Opinion in Structural Biology. 94. 103079–103079. 1 indexed citations

Petraitytė-Burneikienė, Rasa, et al.. (2025). Broadly reactive monoclonal antibodies against beta-lactamases for immunodetection of bacterial resistance to antibiotics. Scientific Reports. 15(1). 19094–19094.

Olechnovič, Kliment, et al.. (2025). FTDMP: A Framework for Protein–Protein, Protein–DNA, and Protein–RNA Docking and Scoring. Proteins Structure Function and Bioinformatics. 2 indexed citations

Dapkūnas, Justas & Mindaugas Margelevičius. (2025). Web-based GTalign: bridging speed and accuracy in protein structure analysis. Nucleic Acids Research. 53(W1). W291–W296. 1 indexed citations

Dapkūnas, Justas, et al.. (2024). PPI3D: a web server for searching, analyzing and modeling protein–protein, protein–peptide and protein–nucleic acid interactions. Nucleic Acids Research. 52(W1). W264–W271. 5 indexed citations

Dapkūnas, Justas, et al.. (2024). Aortic disease and cardiomyopathy in patients with a novel DNMT3A gene variant causing Tatton-Brown–Rahman syndrome. Clinical Epigenetics. 16(1). 76–76. 1 indexed citations

Olechnovič, Kliment, et al.. (2023). Prediction of protein assemblies by structure sampling followed by interface‐focused scoring. Proteins Structure Function and Bioinformatics. 91(12). 1724–1733. 21 indexed citations

Dapkūnas, Justas & Mindaugas Margelevičius. (2022). The COMER web server for protein analysis by homology. Bioinformatics. 39(1). 4 indexed citations

Dapkūnas, Justas, et al.. (2022). PIGN-Related Disease in Two Lithuanian Families: A Report of Two Novel Pathogenic Variants, Molecular and Clinical Characterisation. Medicina. 58(11). 1526–1526. 2 indexed citations

10.

Dapkūnas, Justas, Kliment Olechnovič, & Česlovas Venclovas. (2021). Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction. Proteins Structure Function and Bioinformatics. 89(12). 1834–1843. 13 indexed citations

11.

Kučinskaitė-Kodzė, Indrė, et al.. (2020). Mapping of Recognition Sites of Monoclonal Antibodies Responsible for the Inhibition of Pneumolysin Functional Activity. Biomolecules. 10(7). 1009–1009. 12 indexed citations

12.

Dapkūnas, Justas & Česlovas Venclovas. (2020). Template-Based Modeling of Protein Complexes Using the PPI3D Web Server. Methods in molecular biology. 2165. 139–155. 6 indexed citations

13.

Dapkūnas, Justas, Kliment Olechnovič, & Česlovas Venclovas. (2019). Structural modeling of protein complexes: Current capabilities and challenges. Proteins Structure Function and Bioinformatics. 87(12). 1222–1232. 11 indexed citations

14.

Jiménez‐García, Brian, et al.. (2018). SKEMPI 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation. Bioinformatics. 35(3). 462–469. 218 indexed citations

15.

Grigaitis, Pranas, et al.. (2018). Exogenous interleukin-1α signaling negatively impacts acquired chemoresistance and alters cell adhesion molecule expression pattern in colorectal carcinoma cells HCT116. Cytokine. 114. 38–46. 5 indexed citations

16.

Dapkūnas, Justas, Kliment Olechnovič, & Česlovas Venclovas. (2017). Modeling of protein complexes in CAPRI Round 37 using template‐based approach combined with model selection. Proteins Structure Function and Bioinformatics. 86(S1). 292–301. 11 indexed citations

17.

Moal, Iain H., Justas Dapkūnas, & Juan Fernández‐Recio. (2015). Inferring the microscopic surface energy of protein–protein interfaces from mutation data. Proteins Structure Function and Bioinformatics. 83(4). 640–650. 8 indexed citations

18.

Dapkūnas, Justas, et al.. (2011). QSAR Analysis of Blood–Brain Distribution: The Influence of Plasma and Brain Tissue Binding. Journal of Pharmaceutical Sciences. 100(6). 2147–2160. 45 indexed citations

19.

Didžiapetris, Remigijus, et al.. (2010). Trainable structure–activity relationship model for virtual screening of CYP3A4 inhibition. Journal of Computer-Aided Molecular Design. 24(11). 891–906. 28 indexed citations

20.

Dapkūnas, Justas, et al.. (2009). Probabilistic Prediction of the Human CYP3A4 and CYP2D6 Metabolism Sites. Chemistry & Biodiversity. 6(11). 2101–2106. 10 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