Thomas McGowan

709 total citations
24 papers, 474 citations indexed

About

Thomas McGowan is a scholar working on Spectroscopy, Molecular Biology and Physiology. According to data from OpenAlex, Thomas McGowan has authored 24 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Spectroscopy, 9 papers in Molecular Biology and 3 papers in Physiology. Recurrent topics in Thomas McGowan's work include Advanced Proteomics Techniques and Applications (10 papers), Genomics and Phylogenetic Studies (6 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Thomas McGowan is often cited by papers focused on Advanced Proteomics Techniques and Applications (10 papers), Genomics and Phylogenetic Studies (6 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Thomas McGowan collaborates with scholars based in United States, Germany and Belgium. Thomas McGowan's co-authors include Timothy J. Griffin, Pratik Jagtap, Sean L. Seymour, Joel A. Kooren, Sricharan Bandhakavi, Joel Rudney, Zheng Jin Tu, James E. Johnson, Matthew D. Stone and Subina Mehta and has published in prestigious journals such as Cancer Research, CHEST Journal and Waste Management.

In The Last Decade

Thomas McGowan

24 papers receiving 464 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas McGowan United States 12 325 223 52 49 45 24 474
Kay Schallert Germany 10 346 1.1× 135 0.6× 24 0.5× 116 2.4× 11 0.2× 22 486
Joel A. Kooren United States 5 230 0.7× 156 0.7× 78 1.5× 43 0.9× 64 1.4× 5 355
Bo Liao Canada 4 302 0.9× 97 0.4× 32 0.6× 31 0.6× 8 0.2× 4 346
Karen Culotta France 7 137 0.4× 51 0.2× 13 0.3× 38 0.8× 6 0.1× 8 287
Camille Bellora Luxembourg 7 283 0.9× 37 0.2× 62 1.2× 43 0.9× 2 0.0× 12 374
Brian Bothner United States 11 259 0.8× 15 0.1× 22 0.4× 64 1.3× 12 0.3× 24 468
Desirée Baumgartner Germany 9 252 0.8× 12 0.1× 30 0.6× 102 2.1× 54 1.2× 14 362
Michael Järvå Australia 10 252 0.8× 10 0.0× 15 0.3× 35 0.7× 4 0.1× 17 387
Arlene D. Gonzales United States 7 303 0.9× 119 0.5× 16 0.3× 54 1.1× 1 0.0× 7 419
Michael V. Weinberg United States 10 262 0.8× 24 0.1× 8 0.2× 70 1.4× 3 0.1× 10 426

Countries citing papers authored by Thomas McGowan

Since Specialization
Citations

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

Fields of papers citing papers by Thomas McGowan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas McGowan

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas McGowan. A scholar is included among the top collaborators of Thomas McGowan 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 Thomas McGowan. Thomas McGowan 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.
Issac, Praveen Kumar, James E. Johnson, Thomas McGowan, et al.. (2024). Discovering Novel Proteoforms Using Proteogenomic Workflows Within the Galaxy Bioinformatics Platform. Methods in molecular biology. 2859. 109–128. 1 indexed citations
2.
Mehta, Subina, Praveen Kumar, James E. Johnson, et al.. (2021). Updates on metaQuantome Software for Quantitative Metaproteomics. Journal of Proteome Research. 20(4). 2130–2137. 5 indexed citations
3.
Mehta, Subina, Björn Grüning, James E. Johnson, et al.. (2021). A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19). Clinical Proteomics. 18(1). 15–15. 8 indexed citations
4.
Thuy-Boun, Peter, Subina Mehta, Bjoern Gruening, et al.. (2021). Metaproteomics Analysis of SARS-CoV-2-Infected Patient Samples Reveals Presence of Potential Coinfecting Microorganisms. Journal of Proteome Research. 20(2). 1451–1454. 19 indexed citations
5.
McGowan, Thomas, James E. Johnson, Praveen Kumar, et al.. (2020). Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration. GigaScience. 9(4). 13 indexed citations
6.
Mehta, Subina, Robert J. Millikin, Ignacio Eguinoa, et al.. (2020). Precursor Intensity-Based Label-Free Quantification Software Tools for Proteomic and Multi-Omic Analysis within the Galaxy Platform. Proteomes. 8(3). 15–15. 10 indexed citations
7.
Blank, Clemens, Bjoern Gruening, James E. Johnson, et al.. (2018). Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework. Proteomes. 6(1). 7–7. 27 indexed citations
8.
Chambers, Matthew, Pratik Jagtap, James E. Johnson, et al.. (2017). An Accessible Proteogenomics Informatics Resource for Cancer Researchers. Cancer Research. 77(21). e43–e46. 23 indexed citations
9.
Jagtap, Pratik, et al.. (2013). A two‐step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies. PROTEOMICS. 13(8). 1352–1357. 161 indexed citations
10.
McGowan, Thomas. (2012). Next generation biomass fuel from forest to microchip. 1(1). 1 indexed citations
11.
Jagtap, Pratik, Sricharan Bandhakavi, LeeAnn Higgins, et al.. (2012). Workflow for analysis of high mass accuracy salivary data set using MaxQuant and ProteinPilot search algorithm. PROTEOMICS. 12(11). 1726–1730. 18 indexed citations
12.
Stone, Matthew D., Xiaobing Chen, Thomas McGowan, et al.. (2011). Large-Scale Phosphoproteomics Analysis of Whole Saliva Reveals a Distinct Phosphorylation Pattern. Journal of Proteome Research. 10(4). 1728–1736. 37 indexed citations
13.
Jassim, Rafat Al, Thomas McGowan, Frank M. Andrews, & Catherine McGowan. (2008). Gastric Ulceration in Horses The role of bacteria and lactic acid. Queensland's institutional digital repository (The University of Queensland). 8 indexed citations
14.
McGowan, Catherine, Thomas McGowan, Frank M. Andrews, & Rafat Al Jassim. (2007). Induction and recovery of dietary induced gastric ulcers in horses. Journal of Veterinary Internal Medicine. 21(3). 603–603. 11 indexed citations
15.
McGowan, Thomas. (2004). Charting a Path for Cost-effective NOx Control. Dialnet (Universidad de la Rioja). 111(11). 36–41. 2 indexed citations
16.
McGowan, Thomas. (2003). NOx Control for Stationary Sources and Utility Applications. 677–685. 1 indexed citations
17.
McGowan, Thomas, et al.. (1996). NOx control techniques for the CPI. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 103(6). 98–101. 2 indexed citations
18.
McGowan, Thomas, et al.. (1995). Thermal Encapsulation of Metals in Superfund Soils. Journal of the Air & Waste Management Association. 45(7). 514–520. 3 indexed citations
19.
McGowan, Thomas, et al.. (1982). Construction and startup of a wood gasification pilot plant.. Forest Products Journal. 32(7). 45–50. 2 indexed citations
20.
Greenberg, Charles S., Scott Davies, Thomas McGowan, Anna E. Schorer, & Charles W. Drage. (1979). Acute Respiratory Failure following Severe Arsenic Poisoning. CHEST Journal. 76(5). 596–598. 15 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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