Michael J. Woolley

734 total citations
11 papers, 604 citations indexed

About

Michael J. Woolley is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Michael J. Woolley has authored 11 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 8 papers in Molecular Biology and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Michael J. Woolley's work include Neuropeptides and Animal Physiology (9 papers), Receptor Mechanisms and Signaling (8 papers) and Pharmacological Receptor Mechanisms and Effects (2 papers). Michael J. Woolley is often cited by papers focused on Neuropeptides and Animal Physiology (9 papers), Receptor Mechanisms and Signaling (8 papers) and Pharmacological Receptor Mechanisms and Effects (2 papers). Michael J. Woolley collaborates with scholars based in United Kingdom, New Zealand and United States. Michael J. Woolley's co-authors include Herbert L. Bonkovsky, Alex C. Conner, Debbie L. Hay, Christopher S. Walker, Andrew F. Russo, David R. Poyner, Christopher A. Reynolds, James Barwell, Michael L. Garelja and Juan Carlos Mobarec and has published in prestigious journals such as Journal of Biological Chemistry, Hepatology and Biochemistry.

In The Last Decade

Michael J. Woolley

11 papers receiving 590 citations

Peers

Michael J. Woolley
Anna Mas Spain
Veena Thyagarajan United States
Jonathan M. Koff United States
Melissa Jimenez United States
Min‐Tzu Lo United States
Lucy Goodman New Zealand
Eddy W. H. Yap United States
Michael Volk United States
Anna Mas Spain
Michael J. Woolley
Citations per year, relative to Michael J. Woolley Michael J. Woolley (= 1×) peers Anna Mas

Countries citing papers authored by Michael J. Woolley

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Woolley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Woolley

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

All Works

11 of 11 papers shown
1.
Woolley, Michael J., John Simms, Juan Carlos Mobarec, et al.. (2017). Understanding the molecular functions of the second extracellular loop (ECL2) of the calcitonin gene-related peptide (CGRP) receptor using a comprehensive mutagenesis approach. Molecular and Cellular Endocrinology. 454. 39–49. 4 indexed citations
2.
Woolley, Michael J., Christopher A. Reynolds, John Simms, et al.. (2017). Receptor activity-modifying protein dependent and independent activation mechanisms in the coupling of calcitonin gene-related peptide and adrenomedullin receptors to Gs. Biochemical Pharmacology. 142. 96–110. 29 indexed citations
3.
Walker, Christopher S., et al.. (2017). CGRP receptor antagonist activity of olcegepant depends on the signalling pathway measured. Cephalalgia. 38(3). 437–451. 65 indexed citations
4.
Hasdemir, Burcu, Shilpi Mahajan, Juan A. Osés-Prieto, et al.. (2017). Actin cytoskeleton–dependent regulation of corticotropin-releasing factor receptor heteromers. Molecular Biology of the Cell. 28(18). 2386–2399. 15 indexed citations
6.
Watkins, Harriet A., Joseph J. Gingell, Michael L. Garelja, et al.. (2016). Receptor Activity-modifying Proteins 2 and 3 Generate Adrenomedullin Receptor Subtypes with Distinct Molecular Properties. Journal of Biological Chemistry. 291(22). 11657–11675. 36 indexed citations
7.
Woolley, Michael J. & Alex C. Conner. (2016). Understanding the common themes and diverse roles of the second extracellular loop (ECL2) of the GPCR super-family. Molecular and Cellular Endocrinology. 449. 3–11. 61 indexed citations
8.
Woolley, Michael J. & Alex C. Conner. (2013). Comparing the Molecular Pharmacology of CGRP and Adrenomedullin. Current Protein and Peptide Science. 14(5). 358–374. 20 indexed citations
9.
Woolley, Michael J., Harriet A. Watkins, Bruck Taddese, et al.. (2013). The role of ECL2 in CGRP receptor activation: a combined modelling and experimental approach. Journal of The Royal Society Interface. 10(88). 20130589–20130589. 26 indexed citations
10.
Barwell, James, Michael J. Woolley, Mark Wheatley, Alex C. Conner, & David R. Poyner. (2012). The role of the extracellular loops of the CGRP receptor, a family B GPCR. Biochemical Society Transactions. 40(2). 433–437. 14 indexed citations
11.
Bonkovsky, Herbert L. & Michael J. Woolley. (1999). Reduction of Health–Related Quality of Life in Chronic Hepatitis C and Improvement With Interferon Therapy. Hepatology. 29(1). 264–270. 331 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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