Jesse I. Mobbs

494 total citations
18 papers, 285 citations indexed

About

Jesse I. Mobbs is a scholar working on Molecular Biology, Surgery and Physiology. According to data from OpenAlex, Jesse I. Mobbs has authored 18 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Surgery and 4 papers in Physiology. Recurrent topics in Jesse I. Mobbs's work include Receptor Mechanisms and Signaling (6 papers), Metabolism, Diabetes, and Cancer (4 papers) and Pancreatic function and diabetes (4 papers). Jesse I. Mobbs is often cited by papers focused on Receptor Mechanisms and Signaling (6 papers), Metabolism, Diabetes, and Cancer (4 papers) and Pancreatic function and diabetes (4 papers). Jesse I. Mobbs collaborates with scholars based in Australia, United States and United Kingdom. Jesse I. Mobbs's co-authors include David M. Thal, J.P. Vivian, Anthony W. Purcell, Jamie Rossjohn, Alisa Glukhova, Hariprasad Venugopal, Thomas R. Barber, Radostin Danev, Adrián Cortés and Gil McVean and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Blood.

In The Last Decade

Jesse I. Mobbs

13 papers receiving 284 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jesse I. Mobbs Australia 9 166 92 43 36 27 18 285
Ruobing Ren China 11 215 1.3× 37 0.4× 45 1.0× 38 1.1× 13 0.5× 27 365
Karin E. J. Rödström Sweden 9 178 1.1× 95 1.0× 60 1.4× 10 0.3× 33 1.2× 13 313
Hemlata Dwivedi India 10 213 1.3× 46 0.5× 100 2.3× 16 0.4× 56 2.1× 14 334
Martine Hamel Canada 11 156 0.9× 77 0.8× 26 0.6× 15 0.4× 26 1.0× 12 423
Wenzhong Yan China 12 280 1.7× 29 0.3× 93 2.2× 21 0.6× 19 0.7× 19 433
Tomoaki Komai Japan 10 235 1.4× 114 1.2× 54 1.3× 49 1.4× 14 0.5× 14 492
H Liu China 10 361 2.2× 47 0.5× 90 2.1× 21 0.6× 32 1.2× 21 495
Angqi Zhu China 8 262 1.6× 45 0.5× 41 1.0× 23 0.6× 19 0.7× 12 407
Yayoi Nomura Japan 8 212 1.3× 55 0.6× 83 1.9× 19 0.5× 68 2.5× 14 421
S Varga United States 8 249 1.5× 88 1.0× 31 0.7× 26 0.7× 16 0.6× 19 368

Countries citing papers authored by Jesse I. Mobbs

Since Specialization
Citations

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

Fields of papers citing papers by Jesse I. Mobbs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jesse I. Mobbs. 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 Jesse I. Mobbs. The network helps show where Jesse I. Mobbs may publish in the future.

Co-authorship network of co-authors of Jesse I. Mobbs

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

All Works

18 of 18 papers shown
1.
Braun, Asolina, Jesse I. Mobbs, Sushma Anand, et al.. (2025). A transgenic mouse allows characterization of the HLA-C∗06:02 immunopeptidome in a model of psoriasis. Journal of Investigative Dermatology.
2.
Zhang, Liudi, Jesse I. Mobbs, Hariprasad Venugopal, et al.. (2025). Molecular basis of ligand binding and receptor activation at the human A3 adenosine receptor. Nature Communications. 16(1). 7674–7674.
3.
Venugopal, Hariprasad, Jesse I. Mobbs, Cyntia Taveneau, et al.. (2025). High-resolution cryo-EM using a common LaB 6 120-keV electron microscope equipped with a sub–200-keV direct electron detector. Science Advances. 11(1). eadr0438–eadr0438.
4.
Mobbs, Jesse I., Jinan Wang, Patrick R. Gentry, et al.. (2025). Cryo-EM reveals an extrahelical allosteric binding site at the M5 mAChR. Nature Communications. 16(1). 7046–7046.
5.
Venugopal, Hariprasad, et al.. (2024). Structural insights into the human P2X1 receptor and ligand interactions. Nature Communications. 15(1). 8418–8418. 3 indexed citations
6.
Harikumar, Kaleeckal G., Peishen Zhao, Brian P. Cary, et al.. (2024). Cholesterol-dependent dynamic changes in the conformation of the type 1 cholecystokinin receptor affect ligand binding and G protein coupling. PLoS Biology. 22(7). e3002673–e3002673. 1 indexed citations
7.
Mobbs, Jesse I., Hariprasad Venugopal, Theodore R. Holman, et al.. (2023). Cryo-EM structures of human arachidonate 12S-lipoxygenase bound to endogenous and exogenous inhibitors. Blood. 142(14). 1233–1242. 11 indexed citations
8.
Pham, Vi, Ziva Vuckovic, Alexander S. Powers, et al.. (2023). Xanomeline displays concomitant orthosteric and allosteric binding modes at the M4 mAChR. Nature Communications. 14(1). 5440–5440. 24 indexed citations
9.
Zhang, Liudi, Jesse I. Mobbs, Lauren T. May, Alisa Glukhova, & David M. Thal. (2023). The impact of cryo-EM on determining allosteric modulator-bound structures of G protein-coupled receptors. Current Opinion in Structural Biology. 79. 102560–102560. 20 indexed citations
10.
Anand, Sushma, Dene R. Littler, Jesse I. Mobbs, et al.. (2023). Complimentary electrostatics dominate T-cell receptor binding to a psoriasis-associated peptide antigen presented by human leukocyte antigen C∗06:02. Journal of Biological Chemistry. 299(7). 104930–104930. 4 indexed citations
11.
Mobbs, Jesse I., et al.. (2022). The P2X1 receptor as a therapeutic target. Purinergic Signalling. 18(4). 421–433. 14 indexed citations
12.
Mobbs, Jesse I., Matthew J. Belousoff, Kaleeckal G. Harikumar, et al.. (2021). Structures of the human cholecystokinin 1 (CCK1) receptor bound to Gs and Gq mimetic proteins provide insight into mechanisms of G protein selectivity. PLoS Biology. 19(6). e3001295–e3001295. 47 indexed citations
13.
Gooley, Paul R., Ann Koay, & Jesse I. Mobbs. (2018). Applications of NMR and ITC for the Study of the Kinetics of Carbohydrate Binding by AMPK β-Subunit Carbohydrate-Binding Modules. Methods in molecular biology. 1732. 87–98.
14.
Mobbs, Jesse I., et al.. (2017). Unravelling the Carbohydrate‐Binding Preferences of the Carbohydrate‐Binding Modules of AMP‐Activated Protein Kinase. ChemBioChem. 19(3). 229–238. 3 indexed citations
15.
Kaur, Gurman, Stéphanie Gras, Jesse I. Mobbs, et al.. (2017). Structural and regulatory diversity shape HLA-C protein expression levels. Nature Communications. 8(1). 15924–15924. 77 indexed citations
16.
Mobbs, Jesse I., Patricia T. Illing, Nadine L. Dudek, et al.. (2017). The molecular basis for peptide repertoire selection in the human leukocyte antigen (HLA) C*06:02 molecule. Journal of Biological Chemistry. 292(42). 17203–17215. 35 indexed citations
17.
Mobbs, Jesse I., Ann Koay, Michael Bieri, et al.. (2015). Determinants of oligosaccharide specificity of the carbohydrate-binding modules of AMP-activated protein kinase. Biochemical Journal. 468(2). 245–257. 28 indexed citations
18.
Bieri, Michael, Jesse I. Mobbs, Ann Koay, et al.. (2012). AMP-Activated Protein Kinase β-Subunit Requires Internal Motion for Optimal Carbohydrate Binding. Biophysical Journal. 102(2). 305–314. 18 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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