Nicholas Marze

1.9k total citations
7 papers, 595 citations indexed

About

Nicholas Marze is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Computational Theory and Mathematics. According to data from OpenAlex, Nicholas Marze has authored 7 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computational Theory and Mathematics. Recurrent topics in Nicholas Marze's work include Glycosylation and Glycoproteins Research (3 papers), Protein Structure and Dynamics (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Nicholas Marze is often cited by papers focused on Glycosylation and Glycoproteins Research (3 papers), Protein Structure and Dynamics (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Nicholas Marze collaborates with scholars based in United States, Norway and Japan. Nicholas Marze's co-authors include Jeffrey J. Gray, Maciek R. Antoniewicz, Scott B. Crown, Daisuke Kuroda, Brian D. Weitzner, Sergey Lyskov, Shourya S. Roy Burman, William Sheffler, Jeliazko R. Jeliazkov and Roland L. Dunbrack and has published in prestigious journals such as Bioinformatics, PLoS ONE and Nature Protocols.

In The Last Decade

Nicholas Marze

7 papers receiving 589 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicholas Marze United States 6 447 267 100 49 44 7 595
Trevor Wilkinson United Kingdom 15 427 1.0× 202 0.8× 97 1.0× 27 0.6× 9 0.2× 37 593
Melanie N. Hug Switzerland 10 238 0.5× 141 0.5× 27 0.3× 41 0.8× 21 0.5× 14 439
Nikita V. Ivanisenko Russia 18 484 1.1× 82 0.3× 126 1.3× 33 0.7× 19 0.4× 61 715
Otmar Hainzl Germany 11 965 2.2× 217 0.8× 339 3.4× 25 0.5× 150 3.4× 12 1.2k
Aleksey Nakorchevsky United States 6 716 1.6× 41 0.2× 72 0.7× 30 0.6× 26 0.6× 7 1.2k
D.P. Nannemann United States 12 373 0.8× 79 0.3× 56 0.6× 9 0.2× 63 1.4× 16 556
Elodie Duriez Luxembourg 12 770 1.7× 49 0.2× 150 1.5× 37 0.8× 19 0.4× 13 1.1k
Larissa Doughty Australia 16 410 0.9× 332 1.2× 140 1.4× 135 2.8× 17 0.4× 19 820
E. Krystek Austria 8 345 0.8× 73 0.3× 85 0.8× 16 0.3× 34 0.8× 9 481
Jongsun Jung South Korea 12 413 0.9× 38 0.1× 84 0.8× 63 1.3× 97 2.2× 25 726

Countries citing papers authored by Nicholas Marze

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Marze

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicholas Marze

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

All Works

7 of 7 papers shown
1.
Marze, Nicholas, Shourya S. Roy Burman, William Sheffler, & Jeffrey J. Gray. (2018). Efficient flexible backbone protein–protein docking for challenging targets. Bioinformatics. 34(20). 3461–3469. 116 indexed citations
2.
Burman, Shourya S. Roy, Nicholas Marze, William Sheffler, & Jeffrey J. Gray. (2018). Efficient Flexible-Backbone Docking of Challenging Protein Complexes. Biophysical Journal. 114(3). 344a–344a. 1 indexed citations
3.
Weitzner, Brian D., Jeliazko R. Jeliazkov, Sergey Lyskov, et al.. (2017). Modeling and docking of antibody structures with Rosetta. Nature Protocols. 12(2). 401–416. 199 indexed citations
4.
Marze, Nicholas, Sergey Lyskov, & Jeffrey J. Gray. (2016). Improved prediction of antibody VL–VHorientation. Protein Engineering Design and Selection. 29(10). 409–418. 37 indexed citations
5.
Marze, Nicholas, Jeliazko R. Jeliazkov, Shourya S. Roy Burman, et al.. (2016). Modeling oblong proteins and water‐mediated interfaces with RosettaDock in CAPRI rounds 28–35. Proteins Structure Function and Bioinformatics. 85(3). 479–486. 15 indexed citations
6.
Crown, Scott B., Nicholas Marze, & Maciek R. Antoniewicz. (2015). Catabolism of Branched Chain Amino Acids Contributes Significantly to Synthesis of Odd-Chain and Even-Chain Fatty Acids in 3T3-L1 Adipocytes. PLoS ONE. 10(12). e0145850–e0145850. 150 indexed citations
7.
Weitzner, Brian D., Daisuke Kuroda, Nicholas Marze, Jianqing Xu, & Jeffrey J. Gray. (2014). Blind prediction performance of RosettaAntibody 3.0: Grafting, relaxation, kinematic loop modeling, and full CDR optimization. Proteins Structure Function and Bioinformatics. 82(8). 1611–1623. 77 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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