Michael T. Lerch

1.8k citations
14 papers · 1.2k indexed · 1 hit paper · h-index 9
Topics
Electron Spin Resonance Studies (7 papers)Receptor Mechanisms and Signaling (7 papers)Spectroscopy and Quantum Chemical Studies (3 papers)

In The Last Decade

Michael T. Lerch

11 papers receiving 1.2k citations

Hit Papers

Structural Insights into the Dynamic Process of β2-Adrene...20152026201820222015100200300400500

Peers

Michael T. Lerch
Comparison fields: 5 of 79
  • Molecular Biology 1.1k
  • Cellular and Molecular Neuroscience 552
  • Radiology, Nuclear Medicine and Imaging 181
  • Spectroscopy 169
  • Biophysics 115
Replace Xiao-Jie Yao with:
Xiao-Jie Yao United States
Markus Eilers United States
Dora Toledo Warshaviak United States
Jeffrey J. Liu United States
Alexander Zürn Germany
Kristian Kaufmann United States
Mark A. Wall United States
Gregory V. Nikiforovich United States
Nuška Tschammer Germany
Norzehan Abdul-Manan United States
Michael T. Lerch relative to Xiao-Jie Yao United States Xiao-Jie Yao's profile →
Citations per field
00.5×5.2×
Xiao-Jie Yao · 1×
Citations per year

Countries citing papers authored by Michael T. Lerch

Since Specialization
Citations

This map shows the geographic impact of Michael T. Lerch'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 Michael T. Lerch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael T. Lerch more than expected).

Fields of papers citing papers by Michael T. Lerch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael T. Lerch. 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 Michael T. Lerch. The network helps show where Michael T. Lerch may publish in the future.

Co-authorship network of co-authors of Michael T. Lerch

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 2
5 96
6 34
7 191
8 52
9 37
10 216
11
Structural Insights into the Dynamic Process of β2-Adrenergic Receptor Signalingbreakdown →
521
12 4
13 38
14 40

About Michael T. Lerch

Michael T. Lerch is a scholar working on Biophysics, Physical and Theoretical Chemistry and Virology, having authored 14 papers that have together received 1.2k indexed citations. Recurring topics across this work include Electron Spin Resonance Studies (7 papers), Receptor Mechanisms and Signaling (7 papers) and Spectroscopy and Quantum Chemical Studies (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (552 citations), Biophysics (115 citations) and Molecular Biology (1.1k citations). Michael T. Lerch has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Wayne L. Hubbell, Daniel Hilger, Brian K. Kobilka, Zhongyu Yang, Aashish Manglik, Christian Altenbach, Matthieu Masureel, Tong Sun Kobilka, R. Scott Prosser and Foon Sun Thian. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.

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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