James N. McGuire

431 total citations
17 papers, 349 citations indexed

About

James N. McGuire is a scholar working on Molecular Biology, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, James N. McGuire has authored 17 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Surgery and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in James N. McGuire's work include Pancreatic function and diabetes (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Advanced Proteomics Techniques and Applications (3 papers). James N. McGuire is often cited by papers focused on Pancreatic function and diabetes (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Advanced Proteomics Techniques and Applications (3 papers). James N. McGuire collaborates with scholars based in Denmark, Sweden and United States. James N. McGuire's co-authors include Flemming Pociot, Martin R. Larsen, Anne Julie Overgaard, Jeanne Lainé, Giuseppe Palmisano, Søren Skov Jensen, Peter Rossing, Lise Tarnow, Peter James and Maria Lajer and has published in prestigious journals such as Biochemistry, European Journal of Biochemistry and Molecular & Cellular Proteomics.

In The Last Decade

James N. McGuire

17 papers receiving 345 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James N. McGuire Denmark	12	228	63	58	56	47	17	349
Jiyoung Yu South Korea	10	185 0.8×	49 0.8×	74 1.3×	14 0.3×	26 0.6×	25	332
Paul E. Oran United States	12	234 1.0×	12 0.2×	166 2.9×	56 1.0×	32 0.7×	12	381
Vanna Denti Italy	13	208 0.9×	37 0.6×	171 2.9×	38 0.7×	20 0.4×	32	365
Luana Mercuri Italy	11	176 0.8×	20 0.3×	9 0.2×	62 1.1×	14 0.3×	17	319
Weixing Hu China	12	138 0.6×	34 0.5×	9 0.2×	19 0.3×	32 0.7×	18	404
Aiping Duan China	8	207 0.9×	29 0.5×	13 0.2×	9 0.2×	141 3.0×	15	392
Kazuhiko Fujisawa Japan	7	122 0.5×	29 0.5×	6 0.1×	102 1.8×	17 0.4×	13	431
Jacob Rose United States	12	136 0.6×	29 0.5×	43 0.7×	16 0.3×	7 0.1×	28	259
Andrzej Surus New Zealand	7	155 0.7×	21 0.3×	16 0.3×	168 3.0×	19 0.4×	8	395
Clémence Merlen Canada	11	254 1.1×	17 0.3×	6 0.1×	48 0.9×	21 0.4×	26	414

Countries citing papers authored by James N. McGuire

Since Specialization

Citations

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

Fields of papers citing papers by James N. McGuire

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James N. McGuire. 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 James N. McGuire. The network helps show where James N. McGuire may publish in the future.

Co-authorship network of co-authors of James N. McGuire

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

All Works

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17 of 17 papers shown

McGuire, James N., et al.. (2019). The impact of the glucagon-like peptide 1 receptor agonist liraglutide on the streptozotocin-induced diabetic mouse kidney proteome. Physiological Reports. 7(4). e13994–e13994. 19 indexed citations

Oddo, Alberto, Henning Thøgersen, Leonardo De Maria, et al.. (2018). α-Helix or β-Turn? An Investigation into N-Terminally Constrained Analogues of Glucagon-like Peptide 1 (GLP-1) and Exendin-4. Biochemistry. 57(28). 4148–4154. 11 indexed citations

Norlin, Jenny, et al.. (2017). Effects of insulin and the glucagon‐like peptide 1 receptor agonist liraglutide on the kidney proteome in db/db mice. Physiological Reports. 5(6). 6 indexed citations

Norlin, Jenny, et al.. (2016). N-glycosylation proteome enrichment analysis in kidney reveals differences between diabetic mouse models. Clinical Proteomics. 13(1). 22–22. 15 indexed citations

Palmisano, Giuseppe, Søren Skov Jensen, Jeanne Lainé, et al.. (2012). Characterization of Membrane-shed Microvesicles from Cytokine-stimulated β-Cells Using Proteomics Strategies. Molecular & Cellular Proteomics. 11(8). 230–243. 120 indexed citations

Jensen, Troels Mygind, Daniel R. Witte, Damiana Pieragostino, et al.. (2012). Association between protein signals and type 2 diabetes incidence. Acta Diabetologica. 50(5). 697–704. 9 indexed citations

Overgaard, Anne Julie, James N. McGuire, Peter Hovind, et al.. (2012). Serum amyloid A and C-reactive protein levels may predict microalbuminuria and macroalbuminuria in newly diagnosed type 1 diabetic patients. Journal of Diabetes and its Complications. 27(1). 59–63. 17 indexed citations

Simonsen, Anja Hviid, Sára Bech, Inga Laursen, et al.. (2010). Proteomic investigations of the ventriculo-lumbar gradient in human CSF. Journal of Neuroscience Methods. 191(2). 244–248. 19 indexed citations

Hansen, Henning Gram, Anne Julie Overgaard, Maria Lajer, et al.. (2010). Finding diabetic nephropathy biomarkers in the plasma peptidome by high‐throughput magnetic bead processing and MALDI‐TOF‐MS analysis. PROTEOMICS - CLINICAL APPLICATIONS. 4(8-9). 697–705. 16 indexed citations

10.

McGuire, James N., et al.. (2010). Screening newborns for candidate biomarkers of type 1 diabetes. Archives of Physiology and Biochemistry. 116(4-5). 227–232. 8 indexed citations

11.

Larsen, Claus M., Mirjam Faulenbach, Allan Vaag, et al.. (2010). Serum Proteome Pool Changes in Type 2 Diabetic Patients Treated with Anakinra. Clinical Proteomics. 6(4). 153–161. 1 indexed citations

12.

Overgaard, Anne Julie, Tine E. Thingholm, Martin R. Larsen, et al.. (2010). Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients. Clinical Proteomics. 6(4). 105–114. 26 indexed citations

13.

Overgaard, Anne Julie, Henning Gram Hansen, Maria Lajer, et al.. (2010). Plasma proteome analysis of patients with type 1 diabetes with diabetic nephropathy. Proteome Science. 8(1). 4–4. 33 indexed citations

14.

McGuire, James N., Anne Julie Overgaard, & Flemming Pociot. (2008). Mass spectrometry is only one piece of the puzzle in clinical proteomics. Briefings in Functional Genomics and Proteomics. 7(1). 74–83. 18 indexed citations

15.

Hove‐Jensen, Bjarne & James N. McGuire. (2004). Surface exposed amino acid differences between mesophilic and thermophilic phosphoribosyl diphosphate synthase. European Journal of Biochemistry. 271(22). 4526–4533. 8 indexed citations

16.

McGuire, Kirsten Arnvig, James N. McGuire, & Penny von Wettstein‐Knowles. (2000). Acyl carrier protein (ACP) inhibition and other differences between β-ketoacyl synthase (KAS) I and II. Biochemical Society Transactions. 28(6). 607–610. 11 indexed citations

17.

McGuire, James N., Scott R. Wilson, & Kenneth L. Rinehart. (1995). Cremeomycin, a Novel Cytotoxic Antibiotic from Streptomyces cremeus. Structure Elucidation and Biological Activity.. The Journal of Antibiotics. 48(6). 516–519. 12 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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