Steven D. Brown

17.0k total citations · 3 hit papers
249 papers, 11.8k citations indexed

About

Steven D. Brown is a scholar working on Molecular Biology, Biomedical Engineering and Epidemiology. According to data from OpenAlex, Steven D. Brown has authored 249 papers receiving a total of 11.8k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Molecular Biology, 68 papers in Biomedical Engineering and 46 papers in Epidemiology. Recurrent topics in Steven D. Brown's work include Biofuel production and bioconversion (60 papers), Microbial Metabolic Engineering and Bioproduction (45 papers) and Genomics and Phylogenetic Studies (33 papers). Steven D. Brown is often cited by papers focused on Biofuel production and bioconversion (60 papers), Microbial Metabolic Engineering and Bioproduction (45 papers) and Genomics and Phylogenetic Studies (33 papers). Steven D. Brown collaborates with scholars based in United States, China and Canada. Steven D. Brown's co-authors include Peter Fuchs, Dwayne A. Elias, A L Barry, Arthur L. Barry, Mircea Podar, Anthony V. Palumbo, Maria M. Traczewski, Cynthia C. Gilmour, Richard A. Hurt and Dawn M. Klingeman and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Steven D. Brown

246 papers receiving 11.4k 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.

The Genetic Basis for Bacterial Mercury Methylation

2013 778 citations Jerry M. Parks, Alexander Johs et al. Science profile →
Mercury Methylation by Novel Microorganisms from New Environments

2013 588 citations Mircea Podar, Steven D. Brown et al. profile →
Global prevalence and distribution of genes and microorganisms involved in mercury methylation

2015 359 citations Mircea Podar, Craig C. Brandt et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Steven D. Brown United States	60	3.7k	2.6k	2.4k	2.0k	2.0k	249	11.8k
James A. Imlay United States	69	10.7k 2.9×	1.9k 0.7×	1.8k 0.7×	1.0k 0.5×	1.1k 0.6×	122	22.2k
Raymond J. Turner Canada	60	6.1k 1.6×	1.6k 0.6×	2.2k 0.9×	506 0.3×	1.1k 0.6×	304	16.7k
Hauke Smidt Netherlands	86	14.4k 3.9×	1.6k 0.6×	1.5k 0.6×	1.2k 0.6×	3.1k 1.6×	409	27.0k
Jost Wingender Germany	40	8.8k 2.4×	2.0k 0.8×	2.7k 1.1×	487 0.2×	853 0.4×	74	17.7k
Manuel Simões Portugal	64	6.6k 1.8×	1.5k 0.6×	2.3k 1.0×	302 0.1×	851 0.4×	306	17.2k
Abderrahim Nemmar United Arab Emirates	49	6.0k 1.6×	4.4k 1.7×	1.4k 0.6×	761 0.4×	436 0.2×	207	19.7k
Michael J. Sadowsky United States	83	8.3k 2.2×	2.3k 0.9×	1.1k 0.5×	2.2k 1.1×	4.6k 2.3×	460	25.8k
Min Wu China	59	7.4k 2.0×	651 0.3×	1.6k 0.7×	1.4k 0.7×	759 0.4×	378	14.2k
Roderick I. Mackie United States	68	6.9k 1.9×	560 0.2×	2.3k 1.0×	493 0.2×	1.5k 0.8×	248	17.4k
Tim Tolker‐Nielsen Denmark	72	14.6k 3.9×	665 0.3×	2.0k 0.8×	986 0.5×	1.4k 0.7×	239	20.7k

Countries citing papers authored by Steven D. Brown

Since Specialization

Citations

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

Fields of papers citing papers by Steven D. Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven D. Brown. 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 Steven D. Brown. The network helps show where Steven D. Brown may publish in the future.

Co-authorship network of co-authors of Steven D. Brown

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

All Works

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20 of 20 papers shown

Thompson, R. Adam, Richard J. Giannone, Dana L. Carper, et al.. (2024). Clostridium autoethanogenum alters cofactor synthesis, redox metabolism, and lysine-acetylation in response to elevated H2:CO feedstock ratios for enhancing carbon capture efficiency. SHILAP Revista de lepidopterología. 17(1). 119–119. 5 indexed citations

Sandler, Michael, John T. Sauls, Jeremy W. Schroeder, et al.. (2024). Tools and methods for high-throughput single-cell imaging with the mother machine. eLife. 12. 1 indexed citations

Sandler, Michael, John T. Sauls, Jeremy W. Schroeder, et al.. (2023). Tools and methods for high-throughput single-cell imaging with the mother machine. eLife. 12. 10 indexed citations

Vögeli, Bastian, Luca Schulz, Shivani Garg, et al.. (2022). Cell-free prototyping enables implementation of optimized reverse β-oxidation pathways in heterotrophic and autotrophic bacteria. Nature Communications. 13(1). 3058–3058. 52 indexed citations

Jayakody, Lahiru N., Christopher W. Johnson, Richard J. Giannone, et al.. (2021). Correction: Thermochemical wastewater valorization via enhanced microbial toxicity tolerance. Energy & Environmental Science. 14(12). 6678–6678.

Rodionov, Dmitry A., Irina A. Rodionova, Aleksandr A. Arzamasov, et al.. (2021). Transcriptional Regulation of Plant Biomass Degradation and Carbohydrate Utilization Genes in the Extreme Thermophile Caldicellulosiruptor bescii. mSystems. 6(3). e0134520–e0134520. 15 indexed citations

Vishnivetskaya, Tatiana A., Haiyan Hu, Joy D. Van Nostrand, et al.. (2018). Microbial community structure with trends in methylation gene diversity and abundance in mercury-contaminated rice paddy soils in Guizhou, China. Environmental Science Processes & Impacts. 20(4). 673–685. 49 indexed citations

Jayakody, Lahiru N., Christopher W. Johnson, Richard J. Giannone, et al.. (2018). Thermochemical wastewater valorizationviaenhanced microbial toxicity tolerance. Energy & Environmental Science. 11(6). 1625–1638. 84 indexed citations

Akinosho, Hannah, Alexandru Dumitrache, Jace Natzke, et al.. (2017). Effects of Biomass Accessibility and Klason Lignin Contents during Consolidated Bioprocessing in Populus trichocarpa. ACS Sustainable Chemistry & Engineering. 5(6). 5075–5081. 22 indexed citations

10.

Dumitrache, Alexandru, Allison K. Tolbert, Jace Natzke, et al.. (2017). Cellulose and lignin colocalization at the plant cell wall surface limits microbial hydrolysis of Populus biomass. Green Chemistry. 19(9). 2275–2285. 33 indexed citations

11.

Yoo, Chang Geun, Alexandru Dumitrache, Wellington Muchero, et al.. (2017). Significance of Lignin S/G Ratio in Biomass Recalcitrance of Populus trichocarpa Variants for Bioethanol Production. ACS Sustainable Chemistry & Engineering. 6(2). 2162–2168. 124 indexed citations

12.

Akinosho, Hannah, Chang Geun Yoo, Alexandru Dumitrache, et al.. (2017). Elucidating the Structural Changes toPopulusLignin during Consolidated Bioprocessing withClostridium thermocellum. ACS Sustainable Chemistry & Engineering. 5(9). 7486–7491. 39 indexed citations

13.

Akinosho, Hannah, Kelsey L. Yee, Miguel Rodríguez, et al.. (2017). Lignin Exhibits Recalcitrance‐Associated Features Following the Consolidated Bioprocessing of Populus trichocarpa Natural Variants. ChemistrySelect. 2(33). 10642–10647. 3 indexed citations

14.

Linville, Jessica L., Miguel Rodríguez‐Barranco, Steven D. Brown, Jonathan R. Mielenz, & Chris D. Cox. (2014). Transcriptomic analysis of Clostridium thermocellum Populus hydrolysate-tolerant mutant strain shows increased cellular efficiency in response to Populus hydrolysate compared to the wild type strain. BMC Microbiology. 14(1). 215–215. 9 indexed citations

15.

Parks, Jerry M., Alexander Johs, Mircea Podar, et al.. (2013). The Genetic Basis for Bacterial Mercury Methylation. Science. 339(6125). 1332–1335. 778 indexed citations breakdown →

16.

Yang, Shihui, Richard J. Giannone, Lezlee Dice, et al.. (2012). Clostridium thermocellum ATCC27405 transcriptomic, metabolomic and proteomic profiles after ethanol stress. BMC Genomics. 13(1). 336–336. 63 indexed citations

17.

Torres‐García, Wandaliz, Steven D. Brown, Roger H. Johnson, et al.. (2011). Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis : missing value imputation using temporal datasets. Molecular BioSystems. 7(4). 1093–1104. 9 indexed citations

18.

Yang, Shihui, Miriam Land, Dawn M. Klingeman, et al.. (2010). Paradigm for industrial strain improvement identifies sodium acetate tolerance loci in Zymomonas mobilis and Saccharomyces cerevisiae. Proceedings of the National Academy of Sciences. 107(23). 10395–10400. 93 indexed citations

19.

Brown, Steven D., Melissa Thompson, Nathan C. VerBerkmoes, et al.. (2006). Molecular Dynamics of the Shewanella oneidensis Response to Chromate Stress. Molecular & Cellular Proteomics. 5(6). 1054–1071. 146 indexed citations

20.

Brown, Steven D. & Paul G. Quie. (1981). Investigation of phagocytes in disease. Churchill Livingstone eBooks. 11 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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