Stephen S. Fong

7.1k total citations · 1 hit paper
74 papers, 4.2k citations indexed

About

Stephen S. Fong is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Stephen S. Fong has authored 74 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 29 papers in Biomedical Engineering and 12 papers in Genetics. Recurrent topics in Stephen S. Fong's work include Microbial Metabolic Engineering and Bioproduction (44 papers), Biofuel production and bioconversion (28 papers) and Gene Regulatory Network Analysis (21 papers). Stephen S. Fong is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (44 papers), Biofuel production and bioconversion (28 papers) and Gene Regulatory Network Analysis (21 papers). Stephen S. Fong collaborates with scholars based in United States, Canada and Lebanon. Stephen S. Fong's co-authors include Bernhard Ø. Palsson, Qiang Yan, Andrew R. Joyce, Yinjie Tang, Mattheos Koffas, Corey Largman, Yu Deng, Gang Wu, J. Andrew Jones and Christopher M. Gowen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Stephen S. Fong

73 papers receiving 4.1k citations

Hit Papers

Metabolic Burden: Corners... 2016 2026 2019 2022 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen S. Fong United States 30 3.3k 1.2k 524 288 252 74 4.2k
Eleftherios T. Papoutsakis United States 33 2.2k 0.7× 1.4k 1.2× 447 0.9× 215 0.7× 472 1.9× 92 3.3k
Wei‐Shou Hu United States 31 2.0k 0.6× 625 0.5× 454 0.9× 112 0.4× 90 0.4× 88 3.1k
Martin Vanderlaan United States 32 2.0k 0.6× 393 0.3× 241 0.5× 337 1.2× 163 0.6× 72 3.6k
Nobuhiro Ishida Japan 42 2.6k 0.8× 829 0.7× 324 0.6× 360 1.3× 30 0.1× 94 4.1k
Kirsten Jensen United Kingdom 23 2.0k 0.6× 225 0.2× 487 0.9× 510 1.8× 245 1.0× 42 2.7k
David Sternberg United States 35 2.1k 0.6× 1.1k 0.9× 194 0.4× 645 2.2× 727 2.9× 120 4.6k
Ryan Davis United States 21 1.7k 0.5× 426 0.4× 294 0.6× 240 0.8× 52 0.2× 62 3.0k
Michael J. Betenbaugh United States 55 6.0k 1.9× 1.1k 1.0× 1.0k 2.0× 660 2.3× 45 0.2× 248 8.8k
Gang Wu United States 37 3.0k 0.9× 228 0.2× 552 1.1× 521 1.8× 408 1.6× 151 4.7k
Zhigang Zhou China 36 2.5k 0.8× 396 0.3× 165 0.3× 304 1.1× 220 0.9× 203 4.6k

Countries citing papers authored by Stephen S. Fong

Since Specialization
Citations

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

Fields of papers citing papers by Stephen S. Fong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen S. Fong. 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 Stephen S. Fong. The network helps show where Stephen S. Fong may publish in the future.

Co-authorship network of co-authors of Stephen S. Fong

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen S. Fong. A scholar is included among the top collaborators of Stephen S. Fong 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 Stephen S. Fong. Stephen S. Fong 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
2.
Johnson, Robert D., et al.. (2020). Introduction to the D-SPECT for Technologists: Workflow Using a Dedicated Digital Cardiac Camera. Journal of Nuclear Medicine Technology. 48(4). 297–303. 7 indexed citations
3.
Yan, Qiang, et al.. (2017). Study of ChiR function in Serratia marcescens and its application for improving 2,3-butanediol from crystal chitin. Applied Microbiology and Biotechnology. 101(20). 7567–7578. 12 indexed citations
4.
Miller, Emily Happy, et al.. (2015). Integrative metabolic engineering. SHILAP Revista de lepidopterología. 2(3). 93–103. 2 indexed citations
5.
Yan, Qiang & Stephen S. Fong. (2015). Bacterial chitinase: nature and perspectives for sustainable bioproduction. Bioresources and Bioprocessing. 2(1). 52 indexed citations
6.
Yue, Lili, Zhiming Huang, Stephen S. Fong, et al.. (2015). Targeting ALDH1 to decrease tumorigenicity, growth and metastasis of human melanoma. Melanoma Research. 25(2). 138–148. 51 indexed citations
7.
Senger, Ryan S., et al.. (2014). Designing novel cellulase systems through agent-based modeling and global sensitivity analysis. Bioengineered. 5(4). 243–253. 8 indexed citations
8.
Brooks, J. Paul, et al.. (2012). Gap Detection for Genome-Scale Constraint-Based Models. PubMed. 2012. 1–10. 15 indexed citations
9.
Fisher, Adam, et al.. (2012). Evolutionary Engineering for Industrial Microbiology. Sub-cellular biochemistry. 64. 43–71. 4 indexed citations
10.
Deng, Yu & Stephen S. Fong. (2011). Metabolic engineering of Thermobifida fusca for direct aerobic bioconversion of untreated lignocellulosic biomass to 1-propanol. Metabolic Engineering. 13(5). 570–577. 65 indexed citations
11.
Roberts, Seth B., Christopher M. Gowen, J. Paul Brooks, & Stephen S. Fong. (2010). Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production. BMC Systems Biology. 4(1). 31–31. 89 indexed citations
12.
Roberts, Seth B., et al.. (2010). A Genome‐Scale Metabolic Model of Cryptosporidium hominis. Chemistry & Biodiversity. 7(5). 1026–1039. 18 indexed citations
13.
Fong, Stephen S., et al.. (2010). Synthetic biology. PubMed. 1(5). 309–312. 5 indexed citations
14.
Gowen, Christopher M. & Stephen S. Fong. (2010). Exploring Biodiversity for Cellulosic Biofuel Production. Chemistry & Biodiversity. 7(5). 1086–1097. 32 indexed citations
15.
Bonchev, Danail, et al.. (2010). Cellular Automata Modeling of FASL‐Initiated Apoptosis. Chemistry & Biodiversity. 7(5). 1163–1172. 6 indexed citations
16.
Fong, Stephen S., et al.. (2009). Viral vector-induced expression of bone morphogenetic protein 2 produces inhibition of tumor growth and bone differentiation of stem cells. Cancer Gene Therapy. 17(2). 80–85. 7 indexed citations
17.
Taylor, Dewey, et al.. (2009). Toward a classification of isodynamic feed-forward motifs. Journal of Biological Dynamics. 4(2). 196–211. 2 indexed citations
18.
Hua, Qiang, Andrew R. Joyce, Stephen S. Fong, & Bernhard Ø. Palsson. (2006). Metabolic analysis of adaptive evolution for in silico‐designed lactate‐producing strains. Biotechnology and Bioengineering. 95(5). 992–1002. 51 indexed citations
19.
Herrgård, Markus J., Stephen S. Fong, & Bernhard Ø. Palsson. (2006). Identification of Genome-Scale Metabolic Network Models Using Experimentally Measured Flux Profiles. PLoS Computational Biology. 2(7). e72–e72. 84 indexed citations
20.
Fong, Stephen S., Andrew R. Joyce, & Bernhard Ø. Palsson. (2005). Parallel adaptive evolution cultures ofEscherichia colilead to convergent growth phenotypes with different gene expression states. Genome Research. 15(10). 1365–1372. 212 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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