Martin Maňák

610 total citations
9 papers, 424 citations indexed

About

Martin Maňák is a scholar working on Molecular Biology, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition. According to data from OpenAlex, Martin Maňák has authored 9 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Computer Graphics and Computer-Aided Design and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Martin Maňák's work include Protein Structure and Dynamics (4 papers), Computational Geometry and Mesh Generation (4 papers) and Data Management and Algorithms (2 papers). Martin Maňák is often cited by papers focused on Protein Structure and Dynamics (4 papers), Computational Geometry and Mesh Generation (4 papers) and Data Management and Algorithms (2 papers). Martin Maňák collaborates with scholars based in Czechia, Denmark and Poland. Martin Maňák's co-authors include David Bednář, Jan Brezovský, Barbora Kozlíková, Antonín Pavelka, Jiřı́ Damborský, Lukáš Daniel, Ondřej Strnad, Jan Byška, Sérgio M. Marques and Katarína Furmanová and has published in prestigious journals such as Bioinformatics, Journal of Computational Chemistry and Computer Aided Geometric Design.

In The Last Decade

Martin Maňák

9 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Martin Maňák Czechia	5	301	77	36	34	31	9	424
Jan Byška Czechia	11	347 1.2×	65 0.8×	32 0.9×	41 1.2×	32 1.0×	36	524
Adam Jurčík Czechia	6	253 0.8×	50 0.6×	31 0.9×	29 0.9×	25 0.8×	13	359
Katarína Furmanová Czechia	6	244 0.8×	48 0.6×	30 0.8×	32 0.9×	16 0.5×	23	389
Ondřej Vávra Czechia	9	354 1.2×	74 1.0×	46 1.3×	81 2.4×	21 0.7×	17	467
Qinghua Liao Sweden	13	470 1.6×	120 1.6×	51 1.4×	85 2.5×	43 1.4×	22	655
Lukáš Daniel Czechia	10	456 1.5×	125 1.6×	52 1.4×	49 1.4×	42 1.4×	14	669
Ross Thyer United States	11	457 1.5×	52 0.7×	56 1.6×	26 0.8×	88 2.8×	16	628
Shuichi Fukuyoshi Japan	12	220 0.7×	71 0.9×	57 1.6×	49 1.4×	38 1.2×	60	352
Yana Valasatava Italy	11	489 1.6×	136 1.8×	33 0.9×	91 2.7×	37 1.2×	12	682
João V. Ribeiro United States	5	253 0.8×	70 0.9×	42 1.2×	39 1.1×	19 0.6×	5	406

Countries citing papers authored by Martin Maňák

Since Specialization

Citations

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

Fields of papers citing papers by Martin Maňák

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Maňák

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

All Works

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9 of 9 papers shown

1.

Kolingerová, Ivana, et al.. (2022). Rotational symmetry detection in 3D using reflectional symmetry candidates and quaternion-based rotation parameterization. Computer Aided Geometric Design. 98. 102138–102138. 4 indexed citations

2.

Maňák, Martin, et al.. (2020). Predictive compression of molecular dynamics trajectories. Journal of Molecular Graphics and Modelling. 96. 107531–107531. 6 indexed citations

3.

Maňák, Martin. (2019). Voronoi‐based detection of pockets in proteins defined by large and small probes. Journal of Computational Chemistry. 40(19). 1758–1771. 2 indexed citations

4.

Jurčík, Adam, David Bednář, Jan Byška, et al.. (2018). CAVER Analyst 2.0: analysis and visualization of channels and tunnels in protein structures and molecular dynamics trajectories. Bioinformatics. 34(20). 3586–3588. 273 indexed citations

5.

Maňák, Martin, et al.. (2017). Hybrid Voronoi diagrams, their computation and reduction for applications in computational biochemistry. Journal of Molecular Graphics and Modelling. 74. 225–233. 4 indexed citations

6.

Kolingerová, Ivana, et al.. (2017). Path Planning for Groups on Graphs. Procedia Computer Science. 108. 2338–2342. 1 indexed citations

7.

Maňák, Martin & Ivana Kolingerová. (2015). Extension of the edge tracing algorithm to disconnected Voronoi skeletons. Information Processing Letters. 116(2). 85–92. 6 indexed citations

8.

Kozlíková, Barbora, Eva Šebestová, Vilém Šustr, et al.. (2014). CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures. Bioinformatics. 30(18). 2684–2685. 120 indexed citations

9.

Maňák, Martin & Ivana Kolingerová. (2010). Fast Discovery of Voronoi Vertices in the Construction of Voronoi Diagram of 3D Balls. 95–104. 8 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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