Sandra Murphy

1.2k total citations
43 papers, 854 citations indexed

About

Sandra Murphy is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Sandra Murphy has authored 43 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 19 papers in Cell Biology and 12 papers in Physiology. Recurrent topics in Sandra Murphy's work include Muscle Physiology and Disorders (26 papers), Adipose Tissue and Metabolism (11 papers) and Muscle metabolism and nutrition (10 papers). Sandra Murphy is often cited by papers focused on Muscle Physiology and Disorders (26 papers), Adipose Tissue and Metabolism (11 papers) and Muscle metabolism and nutrition (10 papers). Sandra Murphy collaborates with scholars based in Ireland, Germany and United Kingdom. Sandra Murphy's co-authors include Kay Ohlendieck, Margit Zweyer, Dieter Swandulla, Paul Dowling, Rustam R. Mundegar, Paula Meleady, Michael Henry, Martin D. Curran, Derek Middleton and Ashling Holland and has published in prestigious journals such as Blood, Analytical Biochemistry and Food Research International.

In The Last Decade

Sandra Murphy

42 papers receiving 846 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sandra Murphy Ireland 20 643 360 215 106 100 43 854
Nina Raben United States 6 456 0.7× 174 0.5× 200 0.9× 10 0.1× 18 0.2× 6 942
Evan Boetticher United States 17 437 0.7× 62 0.2× 336 1.6× 35 0.3× 8 0.1× 23 886
Joonseok Cho United States 10 426 0.7× 38 0.1× 176 0.8× 48 0.5× 26 0.3× 16 706
A. Thomas Kovala Canada 13 558 0.9× 197 0.5× 58 0.3× 49 0.5× 11 0.1× 20 750
Akinori Hishiya Japan 13 581 0.9× 124 0.3× 43 0.2× 9 0.1× 8 0.1× 15 738
Federica Chianale Italy 15 380 0.6× 165 0.5× 239 1.1× 18 0.2× 19 0.2× 18 801
K Ii Japan 12 468 0.7× 159 0.4× 104 0.5× 21 0.2× 7 0.1× 25 693
Nicole Taub Austria 11 360 0.6× 187 0.5× 128 0.6× 136 1.3× 4 0.0× 17 750
Elise J. Needham Australia 9 511 0.8× 79 0.2× 113 0.5× 5 0.0× 10 0.1× 11 674
Mohammed Sharif United States 14 322 0.5× 69 0.2× 37 0.2× 32 0.3× 11 0.1× 19 760

Countries citing papers authored by Sandra Murphy

Since Specialization
Citations

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

Fields of papers citing papers by Sandra Murphy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandra Murphy

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

All Works

20 of 20 papers shown
1.
Murphy, Sandra, Thomas Schmitt‐John, Paul Dowling, et al.. (2023). Proteomic profiling of the brain from the <i>wobbler</i> mouse model of amyotrophic lateral sclerosis reveals elevated levels of the astrogliosis marker glial fibrillary acidic protein. European Journal of Translational Myology. 33(3). 1 indexed citations
2.
Murphy, Sandra & Kay Ohlendieck. (2022). Protein Digestion for 2D-DIGE Analysis. Methods in molecular biology. 2596. 339–349. 7 indexed citations
3.
Murphy, Sandra, Margit Zweyer, Dieter Swandulla, & Kay Ohlendieck. (2022). Bioinformatic Analysis of the Subproteomic Profile of Cardiomyopathic Tissue. Methods in molecular biology. 2596. 377–395. 1 indexed citations
4.
Murphy, Sandra & Paul Dowling. (2022). DIGE Analysis of ProteoMiner™ Fractionated Serum/Plasma Samples. Methods in molecular biology. 2596. 119–125. 3 indexed citations
5.
Dowling, Paul, et al.. (2019). Emerging proteomic biomarkers of X-linked muscular dystrophy. Expert Review of Molecular Diagnostics. 19(8). 739–755. 27 indexed citations
6.
Murphy, Sandra, Margit Zweyer, Michael Henry, et al.. (2019). Proteomic profiling of the mouse diaphragm and refined mass spectrometric analysis of the dystrophic phenotype. Journal of Muscle Research and Cell Motility. 40(1). 9–28. 33 indexed citations
7.
Murphy, Sandra, Margit Zweyer, Michael Henry, et al.. (2018). Subproteomic profiling of sarcolemma from dystrophic mdx-4cv skeletal muscle. Data in Brief. 17. 980–993. 6 indexed citations
8.
Murphy, Sandra, Margit Zweyer, Rustam R. Mundegar, Dieter Swandulla, & Kay Ohlendieck. (2018). Proteomic identification of elevated saliva kallikrein levels in the mdx-4cv mouse model of Duchenne muscular dystrophy. Biochemistry and Biophysics Reports. 18. 100541–100541. 15 indexed citations
9.
Murphy, Sandra, Margit Zweyer, Michael Henry, et al.. (2018). Proteomic profiling of liver tissue from the mdx-4cv mouse model of Duchenne muscular dystrophy. Clinical Proteomics. 15(1). 34–34. 26 indexed citations
10.
Murphy, Sandra, Margit Zweyer, Rustam R. Mundegar, Dieter Swandulla, & Kay Ohlendieck. (2018). Dataset on the comparative proteomic profiling of mouse saliva and serum from wild type versus the dystrophic mdx-4cv mouse model of dystrophinopathy. Data in Brief. 21. 1236–1245. 8 indexed citations
11.
Murphy, Sandra, Margit Zweyer, Michael Henry, et al.. (2018). Proteomic analysis of the sarcolemma-enriched fraction from dystrophic mdx-4cv skeletal muscle. Journal of Proteomics. 191. 212–227. 36 indexed citations
12.
Murphy, Sandra & Kay Ohlendieck. (2017). Proteomic profiling of large myofibrillar proteins from dried and long-term stored polyacrylamide gels. Analytical Biochemistry. 543. 8–11. 17 indexed citations
13.
14.
Murphy, Sandra & Kay Ohlendieck. (2017). Protein Digestion for DIGE Analysis. Methods in molecular biology. 1664. 223–232. 4 indexed citations
15.
Murphy, Sandra. (2017). Subcellular Fractionation for DIGE-Based Proteomics. Methods in molecular biology. 1664. 233–243. 1 indexed citations
16.
Murphy, Sandra & Paul Dowling. (2017). DIGE Analysis of ProteoMinerTM Fractionated Serum/Plasma Samples. Methods in molecular biology. 1664. 109–114. 6 indexed citations
17.
Murphy, Sandra & Kay Ohlendieck. (2017). Mass spectrometric identification of dystrophin, the protein product of the Duchenne muscular dystrophy gene, in distinct muscle surface membranes. International Journal of Molecular Medicine. 40(4). 1078–1088. 15 indexed citations
18.
Murphy, Sandra, Paul Dowling, Margit Zweyer, et al.. (2016). Proteomic analysis of dystrophin deficiency and associated changes in the aged mdx-4cv heart model of dystrophinopathy-related cardiomyopathy. Journal of Proteomics. 145. 24–36. 44 indexed citations
19.
Murphy, Sandra, Margit Zweyer, Michael Henry, et al.. (2015). Label-free mass spectrometric analysis reveals complex changes in the brain proteome from the mdx-4cv mouse model of Duchenne muscular dystrophy. Clinical Proteomics. 12(1). 27–27. 27 indexed citations
20.
Murphy, Sandra & Kay Ohlendieck. (2015). The biochemical and mass spectrometric profiling of the dystrophin complexome from skeletal muscle. Computational and Structural Biotechnology Journal. 14. 20–27. 44 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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