Martin Fitzpatrick

710 total citations
19 papers, 510 citations indexed

About

Martin Fitzpatrick is a scholar working on Molecular Biology, Oncology and Infectious Diseases. According to data from OpenAlex, Martin Fitzpatrick has authored 19 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Infectious Diseases. Recurrent topics in Martin Fitzpatrick's work include Metabolomics and Mass Spectrometry Studies (3 papers), Advanced Proteomics Techniques and Applications (2 papers) and Bioinformatics and Genomic Networks (2 papers). Martin Fitzpatrick is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (3 papers), Advanced Proteomics Techniques and Applications (2 papers) and Bioinformatics and Genomic Networks (2 papers). Martin Fitzpatrick collaborates with scholars based in United Kingdom, Netherlands and United States. Martin Fitzpatrick's co-authors include Stephen P. Young, Maarten Altelaar, Albert J. R. Heck, Benjamin A. Fisher, Karim Raza, Andrew Filer, Christopher D. Buckley, Peter C. Taylor, R. F. Sellers and Iain B. McInnes and has published in prestigious journals such as Circulation, Oncogene and Scientific Reports.

In The Last Decade

Martin Fitzpatrick

19 papers receiving 496 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Fitzpatrick United Kingdom 12 267 95 82 80 62 19 510
Bruno Ringel Germany 12 287 1.1× 46 0.5× 112 1.4× 81 1.0× 17 0.3× 15 563
Babylakshmi Muthusamy India 13 311 1.2× 63 0.7× 13 0.2× 84 1.1× 25 0.4× 41 543
Piya Lahiry Canada 10 378 1.4× 77 0.8× 14 0.2× 25 0.3× 26 0.4× 16 642
Lorah Perlee United States 13 242 0.9× 41 0.4× 25 0.3× 78 1.0× 25 0.4× 35 684
M Ohkubo Japan 9 311 1.2× 86 0.9× 33 0.4× 14 0.2× 28 0.5× 16 650
Guang Song China 14 432 1.6× 58 0.6× 55 0.7× 26 0.3× 52 0.8× 24 654
L Chaplin United Kingdom 11 238 0.9× 79 0.8× 26 0.3× 14 0.2× 28 0.5× 15 517
Susanne Ragg United States 11 560 2.1× 123 1.3× 11 0.1× 129 1.6× 31 0.5× 18 708
Ralf Wyrich Germany 13 503 1.9× 60 0.6× 27 0.3× 14 0.2× 28 0.5× 18 716
Virginia Lotti Italy 10 236 0.9× 62 0.7× 35 0.4× 9 0.1× 53 0.9× 32 561

Countries citing papers authored by Martin Fitzpatrick

Since Specialization
Citations

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

Fields of papers citing papers by Martin Fitzpatrick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Fitzpatrick

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Fitzpatrick. A scholar is included among the top collaborators of Martin Fitzpatrick 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 Martin Fitzpatrick. Martin Fitzpatrick 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.
Pancholi, Sunil, Ricardo Ribas, Nikiana Simigdala, et al.. (2020). Tumour kinome re-wiring governs resistance to palbociclib in oestrogen receptor positive breast cancers, highlighting new therapeutic modalities. Oncogene. 39(25). 4781–4797. 63 indexed citations
2.
Fitzpatrick, Martin. (2020). Create GUI Applications with Python & Qt5 (PyQt5 Edition): The hands-on guide to making apps with Python. 1 indexed citations
3.
Bosdriesz, Evert, Joep de Ligt, Sara Mainardi, et al.. (2018). A System-wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells. Molecular & Cellular Proteomics. 17(10). 1892–1908. 13 indexed citations
4.
Fitzpatrick, Martin, et al.. (2018). PaDuA: A Python Library for High-Throughput (Phospho)proteomics Data Analysis. Journal of Proteome Research. 18(2). 576–584. 14 indexed citations
5.
Chiang, David Y., Katherina M. Alsina, Eleonora Corradini, et al.. (2018). Rearrangement of the Protein Phosphatase 1 Interactome During Heart Failure Progression. Circulation. 138(15). 1569–1581. 15 indexed citations
6.
Parreira, José Ricardo, Martin Fitzpatrick, Susana Silvestre, et al.. (2016). Differential proteomics reveals the hallmarks of seed development in common bean ( Phaseolus vulgaris L.). Journal of Proteomics. 143. 188–198. 21 indexed citations
7.
Al‐Ani, Bahjat, Martin Fitzpatrick, Alice M. Coughlan, et al.. (2016). Changes in urinary metabolomic profile during relapsing renal vasculitis. Scientific Reports. 6(1). 38074–38074. 22 indexed citations
8.
Brooks, Jill, Heather M. Long, Claire Shannon‐Lowe, et al.. (2016). Early T Cell Recognition of B Cells following Epstein-Barr Virus Infection: Identifying Potential Targets for Prophylactic Vaccination. PLoS Pathogens. 12(4). e1005549–e1005549. 37 indexed citations
9.
Post, Harm, Renske Penning, Martin Fitzpatrick, et al.. (2016). Robust, Sensitive, and Automated Phosphopeptide Enrichment Optimized for Low Sample Amounts Applied to Primary Hippocampal Neurons. Journal of Proteome Research. 16(2). 728–737. 100 indexed citations
10.
Fitzpatrick, Martin, et al.. (2015). Metabolomic analysis of urine in patients with age related macular degeneration. Investigative Ophthalmology & Visual Science. 56(7). 368–368. 1 indexed citations
11.
Naylor, Andrew S., Saba Nayar, Martin Fitzpatrick, et al.. (2015). A1.17 A novel role for CD248 in controlling the differentiation of follicular dendritic cells (FDCs) following immune challenge. Annals of the Rheumatic Diseases. 74. A7–A8. 1 indexed citations
12.
Fitzpatrick, Martin, Catherine McGrath, & Stephen P. Young. (2014). Pathomx: an interactive workflow-based tool for the analysis of metabolomic data. BMC Bioinformatics. 15(1). 396–396. 17 indexed citations
13.
Fitzpatrick, Martin, et al.. (2013). Metabolomic analysis in patients with age related macular degeneration. Investigative Ophthalmology & Visual Science. 54(15). 3662–3662. 3 indexed citations
14.
Filer, Andrew, Martin Fitzpatrick, Benjamin A. Fisher, et al.. (2013). Metabolic Profiling Predicts Response to Anti–Tumor Necrosis Factor α Therapy in Patients With Rheumatoid Arthritis. Arthritis & Rheumatism. 65(6). 1448–1456. 110 indexed citations
15.
Fitzpatrick, Martin, et al.. (2013). Metabolomics – a novel window into inflammatory disease. Swiss Medical Weekly. 143(304). w13743–w13743. 60 indexed citations
16.
Filer, Andrew, Martin Fitzpatrick, Benjamin A. Fisher, et al.. (2012). PREDICTING RESPONSES TO ANTI-TNF alpha THERAPY IN PATIENTS WITH RHEUMATOID ARTHRITIS USING METABOLOMIC ANALYSIS OF URINE. Lara D. Veeken. 51. 28–28. 4 indexed citations
17.
Dagher, Azar P., Martin Fitzpatrick, Adam E. Flanders, & John Eng. (1998). Enhancing Web applications in radiology with Java: estimating MR imaging relaxation times.. Radiographics. 18(5). 1287–1293. 2 indexed citations
18.
Sellers, R. F. & Martin Fitzpatrick. (1963). Multiplication, Interferon Production and Interferon Sensitivity of Viruses in Dog Kidney Tissue Cultures. Research in Veterinary Science. 4(1). 151–159. 4 indexed citations
19.
Sellers, R. F. & Martin Fitzpatrick. (1962). An assay of interferon produced in rhesus monkey and calf kidney tissue cultures using bovine enterovirus M6 as challenge.. PubMed. 43. 674–83. 22 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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