Mark P. Styczynski

2.3k total citations
68 papers, 1.3k citations indexed

About

Mark P. Styczynski is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Mark P. Styczynski has authored 68 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Molecular Biology, 11 papers in Biomedical Engineering and 7 papers in Genetics. Recurrent topics in Mark P. Styczynski's work include Microbial Metabolic Engineering and Bioproduction (16 papers), Metabolomics and Mass Spectrometry Studies (13 papers) and Gene Regulatory Network Analysis (9 papers). Mark P. Styczynski is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (16 papers), Metabolomics and Mass Spectrometry Studies (13 papers) and Gene Regulatory Network Analysis (9 papers). Mark P. Styczynski collaborates with scholars based in United States, United Kingdom and Canada. Mark P. Styczynski's co-authors include Monica P. McNerney, Gregory Stephanopoulos, Kyle Jensen, Joel F. Moxley, Jason L. Walther, L. Tong, Justin Y. Lee, Yan Zhang, Isidore Rigoutsos and John F. McDonald and has published in prestigious journals such as Nature Communications, Bioinformatics and PLoS ONE.

In The Last Decade

Mark P. Styczynski

67 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark P. Styczynski United States	20	881	272	104	104	84	68	1.3k
Rajnish Kumar India	24	490 0.6×	289 1.1×	52 0.5×	55 0.5×	66 0.8×	116	1.6k
Hiroyuki Kurata Japan	31	2.2k 2.5×	219 0.8×	192 1.8×	85 0.8×	88 1.0×	163	3.0k
Yifei Wang China	18	842 1.0×	131 0.5×	74 0.7×	31 0.3×	73 0.9×	90	1.9k
Xiao‐Jiang Feng United States	17	1.2k 1.3×	200 0.7×	162 1.6×	113 1.1×	253 3.0×	33	2.0k
Javad Zahiri Iran	19	1.1k 1.3×	153 0.6×	91 0.9×	129 1.2×	92 1.1×	62	1.6k
Dong Deng China	16	1.4k 1.5×	138 0.5×	186 1.8×	59 0.6×	213 2.5×	42	2.3k
Steve O’Hagan United Kingdom	21	1.0k 1.2×	216 0.8×	70 0.7×	357 3.4×	47 0.6×	36	1.8k
Paolo Mereghetti Italy	24	1.5k 1.7×	224 0.8×	103 1.0×	41 0.4×	51 0.6×	37	2.2k
Shu‐Yu Lin Taiwan	25	1.4k 1.6×	129 0.5×	121 1.2×	234 2.3×	292 3.5×	94	2.6k

Countries citing papers authored by Mark P. Styczynski

Since Specialization

Citations

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

Fields of papers citing papers by Mark P. Styczynski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark P. Styczynski. 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 Mark P. Styczynski. The network helps show where Mark P. Styczynski may publish in the future.

Co-authorship network of co-authors of Mark P. Styczynski

This figure shows the co-authorship network connecting the top 25 collaborators of Mark P. Styczynski. A scholar is included among the top collaborators of Mark P. Styczynski 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 Mark P. Styczynski. Mark P. Styczynski 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

McSweeney, Megan A., et al.. (2025). A modular cell-free protein biosensor platform using split T7 RNA polymerase. Science Advances. 11(8). eado6280–eado6280. 4 indexed citations

Styczynski, Mark P., et al.. (2024). Assessing structural uncertainty of biochemical regulatory networks in metabolic pathways under varying data quality. npj Systems Biology and Applications. 10(1). 94–94. 1 indexed citations

Verma, Amit, et al.. (2024). Compositional Dependence of DNA Partitioning in a Poly(Ethylene Glycol)–Ficoll Aqueous Two-Phase System. Chemistry. 6(6). 1680–1691.

Styczynski, Mark P., et al.. (2023). Bacillus subtilis engineered for topical delivery of an antifungal agent. PLoS ONE. 18(11). e0293664–e0293664. 2 indexed citations

Zhang, Yan, et al.. (2021). Point-of-Care Analyte Quantification and Digital Readout via Lysate-Based Cell-Free Biosensors Interfaced with Personal Glucose Monitors. ACS Synthetic Biology. 10(11). 2862–2869. 9 indexed citations

Zhang, Yan, et al.. (2021). Metabolic Dynamics in Escherichia coli -Based Cell-Free Systems. ACS Synthetic Biology. 10(9). 2252–2265. 16 indexed citations

McSweeney, Megan A. & Mark P. Styczynski. (2021). Effective Use of Linear DNA in Cell-Free Expression Systems. Frontiers in Bioengineering and Biotechnology. 9. 715328–715328. 19 indexed citations

Lee, Justin Y., et al.. (2020). LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. BMC Bioinformatics. 21(1). 93–93. 5 indexed citations

Joyner, Chester J., Cristiana Ferreira Alves de Brito, Regina Joice Cordy, et al.. (2019). Humoral immunity prevents clinical malaria during Plasmodium relapses without eliminating gametocytes. PLoS Pathogens. 15(9). e1007974–e1007974. 13 indexed citations

10.

Zanetti, Krista A., Robert D. Hall, Julian L. Griffin, et al.. (2019). The Metabolomics Society—Current State of the Membership and Future Directions. Metabolites. 9(5). 89–89. 2 indexed citations

11.

Pires, Pedro Ratto Lisboa, Pâmela A. Alexandre, Amadeu H. Iglesias, et al.. (2019). Identification of a metabolomic signature associated with feed efficiency in beef cattle. BMC Genomics. 20(1). 8–8. 45 indexed citations

12.

Smith, Maren L. & Mark P. Styczynski. (2018). Systems Biology-Based Investigation of Host–Plasmodium Interactions. Trends in Parasitology. 34(7). 617–632. 16 indexed citations

13.

Skolnick, Jeffrey, et al.. (2015). Metabolomics identifies the intersection of phosphoethanolamine with menaquinone-triggered apoptosis in an in vitro model of leukemia. Molecular BioSystems. 11(9). 2406–2416. 27 indexed citations

14.

Styczynski, Mark P., et al.. (2015). Improved metabolite profile smoothing for flux estimation. Molecular BioSystems. 11(9). 2394–2405. 2 indexed citations

15.

Yin, Weiwei, et al.. (2015). A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems. BMC Systems Biology. 9(1). 49–49. 5 indexed citations

16.

Yin, Weiwei, Jessica C. Kissinger, Alberto Moreno, Mary R. Galinski, & Mark P. Styczynski. (2015). From genome-scale data to models of infectious disease: A Bayesian network-based strategy to drive model development. Mathematical Biosciences. 270(Pt B). 156–168. 7 indexed citations

17.

McNerney, Monica P., et al.. (2015). Precise metabolic engineering of carotenoid biosynthesis in Escherichia coli towards a low-cost biosensor. Metabolic Engineering. 31. 171–180. 24 indexed citations

18.

Wang, Lijuan, et al.. (2015). OVCAR-3 Spheroid-Derived Cells Display Distinct Metabolic Profiles. PLoS ONE. 10(2). e0118262–e0118262. 30 indexed citations

19.

Lee, Kevin J., Weiwei Yin, Dalia Arafat, et al.. (2014). Comparative transcriptomics and metabolomics in a rhesus macaque drug administration study. Frontiers in Cell and Developmental Biology. 2. 54–54. 12 indexed citations

20.

Styczynski, Mark P., et al.. (2013). Applications of metabolomics in cancer research. Journal of Carcinogenesis. 12(1). 9–9. 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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