Mette Guldbrandt

440 total citations
9 papers, 365 citations indexed

About

Mette Guldbrandt is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Surgery. According to data from OpenAlex, Mette Guldbrandt has authored 9 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Surgery. Recurrent topics in Mette Guldbrandt's work include Diabetes Treatment and Management (2 papers), Neuropeptides and Animal Physiology (2 papers) and Pancreatic function and diabetes (2 papers). Mette Guldbrandt is often cited by papers focused on Diabetes Treatment and Management (2 papers), Neuropeptides and Animal Physiology (2 papers) and Pancreatic function and diabetes (2 papers). Mette Guldbrandt collaborates with scholars based in Denmark, Ireland and United States. Mette Guldbrandt's co-authors include Søren Berg Padkjær, Per B. Brockhoff, Hanne H. F. Refsgaard, Michael Christensen, David J. Brayden, Ulrik L. Rahbek, Sam Maher, Michael Bur, Nina Hagen and Kwang‐Jin Kim and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and Journal of Medicinal Chemistry.

In The Last Decade

Mette Guldbrandt

9 papers receiving 359 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mette Guldbrandt Denmark 8 159 79 74 68 61 9 365
Jacques Y. Roberge United States 15 343 2.2× 39 0.5× 312 4.2× 14 0.2× 66 1.1× 33 605
Jerry Z. Yang United States 8 103 0.6× 63 0.8× 51 0.7× 19 0.3× 9 0.1× 9 293
Kazuhisa Takayama Japan 12 94 0.6× 154 1.9× 150 2.0× 13 0.2× 25 0.4× 19 415
V. Cioli Italy 11 118 0.7× 31 0.4× 175 2.4× 19 0.3× 24 0.4× 20 517
Alfred Binggeli Switzerland 10 325 2.0× 8 0.1× 102 1.4× 102 1.5× 83 1.4× 10 509
Anthony L. Handlon United States 14 234 1.5× 15 0.2× 191 2.6× 17 0.3× 87 1.4× 20 502
Maria E. Due‐Hansen Denmark 11 384 2.4× 34 0.4× 99 1.3× 33 0.5× 191 3.1× 14 548
Gary R. Manchee United Kingdom 10 174 1.1× 20 0.3× 25 0.3× 15 0.2× 15 0.2× 16 372
Yuanfeng Lyu Hong Kong 7 154 1.0× 14 0.2× 24 0.3× 44 0.6× 22 0.4× 10 359

Countries citing papers authored by Mette Guldbrandt

Since Specialization
Citations

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

Fields of papers citing papers by Mette Guldbrandt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mette Guldbrandt. 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 Mette Guldbrandt. The network helps show where Mette Guldbrandt may publish in the future.

Co-authorship network of co-authors of Mette Guldbrandt

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

All Works

9 of 9 papers shown
1.
Niss, Kristoffer, Sofia Lundh, Jens C. Rekling, et al.. (2022). NPFF Decreases Activity of Human Arcuate NPY Neurons: A Study in Embryonic-Stem-Cell-Derived Model. International Journal of Molecular Sciences. 23(6). 3260–3260. 7 indexed citations
2.
Murray, Sara A., Louise S. Dalbøge, Karalee Baquero, et al.. (2020). Whole transcriptome analysis and validation of metabolic pathways in subcutaneous adipose tissues during FGF21-induced weight loss in non-human primates. Scientific Reports. 10(1). 7287–7287. 8 indexed citations
3.
Rahbek, Ulrik L., et al.. (2013). Colonic absorption of salmon calcitonin using tetradecyl maltoside (TDM) as a permeation enhancer. European Journal of Pharmaceutical Sciences. 48(4-5). 726–734. 25 indexed citations
4.
Maher, Sam, et al.. (2012). Evaluation of alkylmaltosides as intestinal permeation enhancers: Comparison between rat intestinal mucosal sheets and Caco-2 monolayers. European Journal of Pharmaceutical Sciences. 47(4). 701–712. 56 indexed citations
5.
Madsen, Peter, János T. Kodra, Carsten Behrens, et al.. (2009). Human Glucagon Receptor Antagonists with Thiazole Cores. A Novel Series with Superior Pharmacokinetic Properties. Journal of Medicinal Chemistry. 52(9). 2989–3000. 26 indexed citations
6.
Kodra, János T., Anker Jørgensen, Birgitte Andersen, et al.. (2008). Novel Glucagon Receptor Antagonists with Improved Selectivity over the Glucose-Dependent Insulinotropic Polypeptide Receptor. Journal of Medicinal Chemistry. 51(17). 5387–5396. 43 indexed citations
7.
Bur, Michael, Hanno Huwer, Claus‐Michael Lehr, et al.. (2006). Assessment of transport rates of proteins and peptides across primary human alveolar epithelial cell monolayers. European Journal of Pharmaceutical Sciences. 28(3). 196–203. 41 indexed citations
8.
Refsgaard, Hanne H. F., et al.. (2005). In Silico Prediction of Membrane Permeability from Calculated Molecular Parameters. Journal of Medicinal Chemistry. 48(3). 805–811. 153 indexed citations
9.
Guldbrandt, Mette, Tommy N. Johansen, Karla Frydenvang, et al.. (2002). Glutamate receptor ligands: Synthesis, stereochemistry, and enantiopharmacology of methylated 2‐aminoadipic acid analogs. Chirality. 14(4). 351–363. 6 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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