John G. Logan

3.4k total citations
19 papers, 513 citations indexed

About

John G. Logan is a scholar working on Molecular Biology, Oncology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, John G. Logan has authored 19 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 10 papers in Oncology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in John G. Logan's work include Bone Metabolism and Diseases (10 papers), Bone health and treatments (8 papers) and Thyroid Disorders and Treatments (4 papers). John G. Logan is often cited by papers focused on Bone Metabolism and Diseases (10 papers), Bone health and treatments (8 papers) and Thyroid Disorders and Treatments (4 papers). John G. Logan collaborates with scholars based in United Kingdom, Australia and United States. John G. Logan's co-authors include Silvia Marino, David Mellis, Mattia Capulli, Graham R. Williams, Aymen I. Idris, J. H. Duncan Bassett, Patrick Mollat, Stuart H. Ralston, Peter I. Croucher and David A. Fidock and has published in prestigious journals such as Journal of Biological Chemistry, Endocrinology and Molecular Microbiology.

In The Last Decade

John G. Logan

19 papers receiving 505 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John G. Logan United Kingdom 13 262 126 115 62 56 19 513
Yisong Wang China 12 258 1.0× 94 0.7× 39 0.3× 27 0.4× 14 0.3× 28 504
Sébastien Soubeyrand Canada 18 520 2.0× 152 1.2× 116 1.0× 61 1.0× 3 0.1× 37 832
Hella Kohlhof Germany 16 482 1.8× 136 1.1× 20 0.2× 9 0.1× 21 0.4× 40 686
Charity L. Washam United States 11 335 1.3× 274 2.2× 32 0.3× 7 0.1× 9 0.2× 27 667
Cassandra M. Thumwood Australia 7 138 0.5× 143 1.1× 165 1.4× 24 0.4× 11 0.2× 10 468
Joern-Peter Halle Germany 12 351 1.3× 82 0.7× 13 0.1× 38 0.6× 15 0.3× 24 562
James McCabe United States 11 348 1.3× 202 1.6× 23 0.2× 15 0.2× 6 0.1× 14 622
Edmond M. Linossi Australia 11 231 0.9× 251 2.0× 21 0.2× 22 0.4× 5 0.1× 17 551
Daniela I. Staquicini United States 10 183 0.7× 35 0.3× 71 0.6× 27 0.4× 7 0.1× 18 374

Countries citing papers authored by John G. Logan

Since Specialization
Citations

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

Fields of papers citing papers by John G. Logan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Logan. 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 John G. Logan. The network helps show where John G. Logan may publish in the future.

Co-authorship network of co-authors of John G. Logan

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

All Works

19 of 19 papers shown
1.
Pereira, Marie, Jeong‐Hun Ko, John G. Logan, et al.. (2020). A trans-eQTL network regulates osteoclast multinucleation and bone mass. eLife. 9. 23 indexed citations
2.
Freudenthal, Bernard, Natalie C. Butterfield, John G. Logan, et al.. (2019). Genetic and Pharmacological Targeting of Transcriptional Repression in Resistance to Thyroid Hormone Alpha. Thyroid. 29(5). 726–734. 8 indexed citations
3.
Marino, Silvia, et al.. (2019). Pharmacological Inhibition of NFκB Reduces Prostate Cancer Related Osteoclastogenesis In Vitro and Osteolysis Ex Vivo. Calcified Tissue International. 105(2). 193–204. 19 indexed citations
4.
Butterfield, Natalie C., John G. Logan, Julian Waung, Graham R. Williams, & J. H. Duncan Bassett. (2019). Quantitative X-Ray Imaging of Mouse Bone by Faxitron. Methods in molecular biology. 1914. 559–569. 10 indexed citations
5.
Leitch, Victoria D., Sofia Rahman, Natalie C. Butterfield, et al.. (2019). PYY is a negative regulator of bone mass and strength. Bone. 127. 427–435. 13 indexed citations
6.
Marino, Silvia, Ryan T. Bishop, Mattia Capulli, et al.. (2018). Regulation of breast cancer induced bone disease by cancer-specific IKKβ. Oncotarget. 9(22). 16134–16148. 5 indexed citations
7.
Marino, Silvia, Ryan T. Bishop, John G. Logan, Patrick Mollat, & Aymen I. Idris. (2017). Pharmacological evidence for the bone-autonomous contribution of the NFκB/β-catenin axis to breast cancer related osteolysis. Cancer Letters. 410. 180–190. 12 indexed citations
8.
Freudenthal, Bernard, et al.. (2016). Rapid phenotyping of knockout mice to identify genetic determinants of bone strength. Journal of Endocrinology. 231(1). R31–R46. 19 indexed citations
9.
Sophocleous, Antonia, Silvia Marino, John G. Logan, et al.. (2015). Bone Cell-autonomous Contribution of Type 2 Cannabinoid Receptor to Breast Cancer-induced Osteolysis. Journal of Biological Chemistry. 290(36). 22049–22060. 32 indexed citations
10.
Bassett, J. H. Duncan, Anne H. van der Spek, John G. Logan, et al.. (2015). Thyrostimulin Regulates Osteoblastic Bone Formation During Early Skeletal Development. Endocrinology. 156(9). 3098–3113. 32 indexed citations
11.
Waung, Julian, Stephanie A. Maynard, Sahana Gopal, et al.. (2014). Quantitative X-ray microradiography for high-throughput phenotyping of osteoarthritis in mice. Osteoarthritis and Cartilage. 22(10). 1396–1400. 12 indexed citations
12.
Gogakos, Apostolos, John G. Logan, Julian Waung, et al.. (2014). THRA and DIO2 mutations are unlikely to be a common cause of increased bone mineral density in euthyroid post-menopausal women. European Journal of Endocrinology. 170(4). 637–644. 6 indexed citations
13.
Marino, Silvia, John G. Logan, David Mellis, & Mattia Capulli. (2014). Generation and culture of osteoclasts. BoneKEy Reports. 3(2011). 570–570. 88 indexed citations
14.
OʼShea, Patrick, Dong Wook Kim, John G. Logan, et al.. (2012). Advanced Bone Formation in Mice with a Dominant-negative Mutation in the Thyroid Hormone Receptor β Gene due to Activation of Wnt/β-Catenin Protein Signaling. Journal of Biological Chemistry. 287(21). 17812–17822. 32 indexed citations
15.
Bassett, J. H. Duncan, John G. Logan, A. Boyde, et al.. (2012). Mice Lacking the Calcineurin Inhibitor Rcan2 Have an Isolated Defect of Osteoblast Function. Endocrinology. 153(7). 3537–3548. 23 indexed citations
16.
Logan, John G., Antonia Sophocleous, Silvia Marino, et al.. (2012). Selective tyrosine kinase inhibition of insulin-like growth factor-1 receptor inhibits human and mouse breast cancer–induced bone cell activity, bone remodeling, and osteolysis. Journal of Bone and Mineral Research. 28(5). 1229–1242. 14 indexed citations
17.
Frantzias, Joseph, John G. Logan, Patrick Mollat, et al.. (2011). Hydrogen sulphide‐releasing diclofenac derivatives inhibit breast cancer‐induced osteoclastogenesis in vitro and prevent osteolysis ex vivo. British Journal of Pharmacology. 165(6). 1914–1925. 37 indexed citations
18.
19.
Hunt, Paul, Ana Afonso, Alison M. Creasey, et al.. (2007). Gene encoding a deubiquitinating enzyme is mutated in artesunate‐ and chloroquine‐resistant rodent malaria parasites§. Molecular Microbiology. 65(1). 27–40. 127 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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