Frederick H. Strobel

2.2k total citations · 1 hit paper
13 papers, 1.7k citations indexed

About

Frederick H. Strobel is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Frederick H. Strobel has authored 13 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Pathology and Forensic Medicine and 2 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Frederick H. Strobel's work include Metabolomics and Mass Spectrometry Studies (8 papers), Adenosine and Purinergic Signaling (2 papers) and Mitochondrial Function and Pathology (2 papers). Frederick H. Strobel is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (8 papers), Adenosine and Purinergic Signaling (2 papers) and Mitochondrial Function and Pathology (2 papers). Frederick H. Strobel collaborates with scholars based in United States, South Korea and China. Frederick H. Strobel's co-authors include Dean P. Jones, Quinlyn A. Soltow, Youngja Park, Shuzhao Li, Sai Duraisingham, Nooruddin Khan, Bali Pulendran, Karan Uppal, Tianwei Yu and Kim M. Gernert and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Arteriosclerosis Thrombosis and Vascular Biology.

In The Last Decade

Frederick H. Strobel

13 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting Network Activity from High Throughput Metabolomics

2013 664 citations Shuzhao Li, Youngja Park et al. PLoS Computational Biology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Frederick H. Strobel United States	10	1.0k	387	263	209	134	13	1.7k
Quinlyn A. Soltow United States	23	1.4k 1.4×	376 1.0×	596 2.3×	210 1.0×	123 0.9×	33	2.6k
Carolina Fernández United States	22	1.2k 1.2×	366 0.9×	313 1.2×	99 0.5×	67 0.5×	40	2.2k
Jennifer Kirwan Germany	21	1.1k 1.0×	110 0.3×	199 0.8×	84 0.4×	290 2.2×	52	1.6k
Hemi Luan China	20	682 0.7×	192 0.5×	182 0.7×	34 0.2×	108 0.8×	39	1.3k
Kévin Contrepois United States	22	1.0k 1.0×	92 0.2×	379 1.4×	102 0.5×	184 1.4×	45	2.0k
Julia Yue Cui United States	34	1.7k 1.6×	395 1.0×	444 1.7×	110 0.5×	49 0.4×	89	3.1k
Xiaotao Shen China	22	1.3k 1.3×	114 0.3×	252 1.0×	75 0.4×	413 3.1×	36	2.1k
Joana Pinto Portugal	23	922 0.9×	81 0.2×	196 0.7×	81 0.4×	238 1.8×	94	1.9k
Stewart F. Graham United States	30	1.5k 1.5×	84 0.2×	695 2.6×	109 0.5×	84 0.6×	106	2.8k
Xin Hu United States	24	445 0.4×	574 1.5×	131 0.5×	91 0.4×	20 0.1×	83	1.4k

Countries citing papers authored by Frederick H. Strobel

Since Specialization

Citations

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

Fields of papers citing papers by Frederick H. Strobel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frederick H. Strobel. 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 Frederick H. Strobel. The network helps show where Frederick H. Strobel may publish in the future.

Co-authorship network of co-authors of Frederick H. Strobel

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

All Works

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13 of 13 papers shown

Liu, Ken, Choon‐Myung Lee, Edward T. Morgan, et al.. (2024). Mammalian hydroxylation of microbiome-derived obesogen, delta-valerobetaine, to homocarnitine, a 5-carbon carnitine analog. Journal of Biological Chemistry. 301(1). 108074–108074. 1 indexed citations

Sayegh, Michael N., Kimberly A. Cooney, Woojin M. Han, et al.. (2023). Hydrogel delivery of purinergic enzymes improves cardiac ischemia/reperfusion injury. Journal of Molecular and Cellular Cardiology. 176. 98–109. 7 indexed citations

Sayegh, Michael N., Kimberly A. Cooney, Woojin M. Han, et al.. (2021). A Hydrogel Strategy to Augment Tissue Adenosine to Improve Hindlimb Perfusion. Arteriosclerosis Thrombosis and Vascular Biology. 41(6). e314–e324. 2 indexed citations

Shin, Eric, Lanfang Wang, Marina Zemskova, et al.. (2018). Adenosine Production by Biomaterial‐Supported Mesenchymal Stromal Cells Reduces the Innate Inflammatory Response in Myocardial Ischemia/Reperfusion Injury. Journal of the American Heart Association. 7(2). 51 indexed citations

Go, Young‐Mi, Douglas I. Walker, Yongliang Liang, et al.. (2015). Reference Standardization for Mass Spectrometry and High-resolution Metabolomics Applications to Exposome Research. Toxicological Sciences. 148(2). 531–543. 188 indexed citations

Go, Young‐Mi, Karan Uppal, Douglas I. Walker, et al.. (2014). Mitochondrial Metabolomics Using High-Resolution Fourier-Transform Mass Spectrometry. Methods in molecular biology. 1198. 43–73. 38 indexed citations

Uppal, Karan, Quinlyn A. Soltow, Frederick H. Strobel, et al.. (2013). xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data. BMC Bioinformatics. 14(1). 15–15. 283 indexed citations

Li, Shuzhao, Youngja Park, Sai Duraisingham, et al.. (2013). Predicting Network Activity from High Throughput Metabolomics. PLoS Computational Biology. 9(7). e1003123–e1003123. 664 indexed citations breakdown →

Roede, James R., Karan Uppal, Youngja Park, et al.. (2013). Serum Metabolomics of Slow vs. Rapid Motor Progression Parkinson’s Disease: a Pilot Study. PLoS ONE. 8(10). e77629–e77629. 104 indexed citations

10.

Park, Youngja, Kichun Lee, Quinlyn A. Soltow, et al.. (2012). High-performance metabolic profiling of plasma from seven mammalian species for simultaneous environmental chemical surveillance and bioeffect monitoring. Toxicology. 295(1-3). 47–55. 71 indexed citations

11.

Roede, James R., Youngja Park, Shuzhao Li, Frederick H. Strobel, & Dean P. Jones. (2012). Detailed Mitochondrial Phenotyping by High Resolution Metabolomics. PLoS ONE. 7(3). e33020–e33020. 38 indexed citations

12.

Soltow, Quinlyn A., Frederick H. Strobel, Keith G. Mansfield, et al.. (2011). High-performance metabolic profiling with dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) for study of the exposome. Metabolomics. 9(S1). 132–143. 144 indexed citations

13.

Johnson, Jennifer M., Tianwei Yu, Frederick H. Strobel, & Dean P. Jones. (2010). A practical approach to detect unique metabolic patterns for personalized medicine. The Analyst. 135(11). 2864–2864. 82 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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