Morgan Lawrenz

847 citations
12 papers · 639 indexed · h-index 10
Topics
Protein Structure and Dynamics (8 papers)Computational Drug Discovery Methods (4 papers)Receptor Mechanisms and Signaling (3 papers)
Partner nations
United States

In The Last Decade

Morgan Lawrenz

12 papers receiving 628 citations

Peers

Morgan Lawrenz
Comparison fields: 5 of 82
  • Molecular Biology 545
  • Computational Theory and Mathematics 121
  • Spectroscopy 114
  • Materials Chemistry 98
  • Cellular and Molecular Neuroscience 91
Replace Martin K. Scherer with:
Martin K. Scherer Germany
Servaas Michielssens Belgium
Robert G. Smock United States
Yu‐Chu Chang United States
Larisa Adamian United States
Michele Seeber Italy
David E. Konerding United States
Ignasi Buch Spain
Lane Votapka United States
Hendrik R. A. Jonker Germany
Morgan Lawrenz relative to Martin K. Scherer Germany Martin K. Scherer's profile →
Citations per field
00.5×2.9×
Martin K. Scherer · 1×
Citations per year

Countries citing papers authored by Morgan Lawrenz

Since Specialization
Citations

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

Fields of papers citing papers by Morgan Lawrenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Morgan Lawrenz

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 1
2 43
3 11
4 43
5 330
6 26
7 11
8 15
9 43
10 33
11 79
12 4

About Morgan Lawrenz

Morgan Lawrenz is a scholar working on Computational Theory and Mathematics, Spectroscopy and Statistical and Nonlinear Physics, having authored 12 papers that have together received 639 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Computational Drug Discovery Methods (4 papers) and Receptor Mechanisms and Signaling (3 papers). The work is most often cited by research in Molecular Biology (545 citations), Computational Theory and Mathematics (121 citations) and Spectroscopy (114 citations). Morgan Lawrenz has collaborated with scholars based in United States. Frequent co-authors include Vijay S. Pande, Diwakar Shukla, J. Andrew McCammon, Gregory R. Bowman, Dan Belov, Russ B. Altman, David E. Konerding, Kai Kohlhoff, Riccardo Baron and Jeff Wereszczynski. Their work appears in journals such as Nature Communications, Chemical Communications and Scientific Reports.

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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