Michael T. Lerch

1.8k total citations · 1 hit paper
14 papers, 1.2k citations indexed

About

Michael T. Lerch is a scholar working on Molecular Biology, Biophysics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Michael T. Lerch has authored 14 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Biophysics and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Michael T. Lerch's work include Electron Spin Resonance Studies (7 papers), Receptor Mechanisms and Signaling (7 papers) and Spectroscopy and Quantum Chemical Studies (3 papers). Michael T. Lerch is often cited by papers focused on Electron Spin Resonance Studies (7 papers), Receptor Mechanisms and Signaling (7 papers) and Spectroscopy and Quantum Chemical Studies (3 papers). Michael T. Lerch collaborates with scholars based in United States, Canada and Australia. Michael T. Lerch's 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 and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Michael T. Lerch

11 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Structural Insights into the Dynamic Process of β2-Adrenergic Receptor Signaling

2015 521 citations Aashish Manglik, Tae Hun Kim et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael T. Lerch United States	9	1.1k	552	181	169	115	14	1.2k
Markus Eilers United States	23	1.8k 1.7×	981 1.8×	154 0.9×	284 1.7×	51 0.4×	31	2.1k
Xiao-Jie Yao United States	5	1.5k 1.4×	842 1.5×	272 1.5×	139 0.8×	22 0.2×	10	1.6k
Yutaka Kofuku Japan	15	1.0k 1.0×	465 0.8×	194 1.1×	210 1.2×	25 0.2×	25	1.1k
Harini Krishnamurthy United States	10	857 0.8×	418 0.8×	57 0.3×	135 0.8×	32 0.3×	11	1.1k
Jeffrey J. Liu United States	10	1.0k 0.9×	558 1.0×	136 0.8×	164 1.0×	48 0.4×	12	1.1k
Ansgar Wegener Germany	19	1.0k 1.0×	642 1.2×	73 0.4×	177 1.0×	86 0.7×	27	1.5k
Gregory V. Nikiforovich United States	26	1.4k 1.3×	597 1.1×	218 1.2×	209 1.2×	38 0.3×	92	1.9k
Dora Toledo Warshaviak United States	16	755 0.7×	146 0.3×	130 0.7×	47 0.3×	92 0.8×	20	1.1k
Shin Isogai Japan	11	882 0.8×	138 0.3×	102 0.6×	169 1.0×	37 0.3×	17	1.0k
Mark A. Wall United States	6	913 0.9×	202 0.4×	48 0.3×	51 0.3×	192 1.7×	8	1.1k

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

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14 of 14 papers shown

Mett, Richard R., et al.. (2025). A high‐sensitivity stopped‐flow EPR system to monitor millisecond conformational kinetics in spin‐labeled proteins. Protein Science. 34(8). e70214–e70214.

Xu, Jun, Ruoyi Qiu, Harald Hübner, et al.. (2025). The Role of Intrinsically Disordered Domains in Regulating G Protein-Coupled Receptor Signaling. Journal of the American Chemical Society. 148(1). 1430–1443.

Brennan, Patrick, et al.. (2025). Capturing protein dynamics across timescales with site-directed spin labeling electron paramagnetic resonance spectroscopy. Current Opinion in Structural Biology. 93. 103073–103073.

Sidabras, Jason W., Christian Altenbach, Richard R. Mett, et al.. (2024). A pressure‐jump EPR system to monitor millisecond conformational exchange rates of spin‐labeled proteins. Protein Science. 33(12). e5220–e5220. 2 indexed citations

Hilger, Daniel, Kaavya Krishna Kumar, Hongli Hu, et al.. (2020). Structural insights into differences in G protein activation by family A and family B GPCRs. Science. 369(6503). 96 indexed citations

Lerch, Michael T., Rachel A. Matt, Matthieu Masureel, et al.. (2020). Viewing rare conformations of the β ₂ adrenergic receptor with pressure-resolved DEER spectroscopy. Proceedings of the National Academy of Sciences. 117(50). 31824–31831. 34 indexed citations

Wingler, Laura M., Matthias Elgeti, Daniel Hilger, et al.. (2019). Angiotensin Analogs with Divergent Bias Stabilize Distinct Receptor Conformations. Cell. 176(3). 468–478.e11. 191 indexed citations

Stadtmueller, Beth M., Michael D. Bridges, Kim-Marie A. Dam, et al.. (2018). DEER Spectroscopy Measurements Reveal Multiple Conformations of HIV-1 SOSIP Envelopes that Show Similarities with Envelopes on Native Virions. Immunity. 49(2). 235–246.e4. 52 indexed citations

Bergdoll, Lucie, Michael T. Lerch, John W. Patrick, et al.. (2017). Protonation state of glutamate 73 regulates the formation of a specific dimeric association of mVDAC1. Proceedings of the National Academy of Sciences. 115(2). E172–E179. 37 indexed citations

10.

Dror, Ron O., Thomas J. Mildorf, Daniel Hilger, et al.. (2015). Structural basis for nucleotide exchange in heterotrimeric G proteins. Science. 348(6241). 1361–1365. 216 indexed citations

11.

Manglik, Aashish, Tae Hun Kim, Matthieu Masureel, et al.. (2015). Structural Insights into the Dynamic Process of β2-Adrenergic Receptor Signaling. Cell. 161(5). 1101–1111. 521 indexed citations breakdown →

12.

Manglik, Aashish, Tae Hun Kim, Matthieu Masureel, et al.. (2015). Structural Insights into the Dynamic Process of β2-Adrenergic Receptor Signaling. Cell. 162(6). 1431–1431. 4 indexed citations

13.

Lerch, Michael T., Zhongyu Yang, Evan K. Brooks, & Wayne L. Hubbell. (2014). Mapping protein conformational heterogeneity under pressure with site-directed spin labeling and double electron–electron resonance. Proceedings of the National Academy of Sciences. 111(13). E1201–10. 38 indexed citations

14.

Lerch, Michael T., Joseph Horwitz, John J. McCoy, & Wayne L. Hubbell. (2013). Circular dichroism and site-directed spin labeling reveal structural and dynamical features of high-pressure states of myoglobin. Proceedings of the National Academy of Sciences. 110(49). E4714–22. 40 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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