Nanette Boyle

2.1k total citations
31 papers, 1.5k citations indexed

About

Nanette Boyle is a scholar working on Molecular Biology, Renewable Energy, Sustainability and the Environment and Biomedical Engineering. According to data from OpenAlex, Nanette Boyle has authored 31 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 20 papers in Renewable Energy, Sustainability and the Environment and 5 papers in Biomedical Engineering. Recurrent topics in Nanette Boyle's work include Algal biology and biofuel production (20 papers), Microbial Metabolic Engineering and Bioproduction (18 papers) and Photosynthetic Processes and Mechanisms (11 papers). Nanette Boyle is often cited by papers focused on Algal biology and biofuel production (20 papers), Microbial Metabolic Engineering and Bioproduction (18 papers) and Photosynthetic Processes and Mechanisms (11 papers). Nanette Boyle collaborates with scholars based in United States, Germany and Canada. Nanette Boyle's co-authors include John A. Morgan, Janette Kropat, David Casero, Matteo Pellegrini, Ian K. Blaby, Arthur Grossman, Sabeeha Merchant, Shannon L. Johnson, Sean D. Gallaher and Christoph Benning and has published in prestigious journals such as Journal of Biological Chemistry, Nature Biotechnology and PLoS ONE.

In The Last Decade

Nanette Boyle

31 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nanette Boyle United States 15 1.2k 994 248 213 160 31 1.5k
Li Wei China 18 952 0.8× 1.0k 1.0× 176 0.7× 124 0.6× 151 0.9× 46 1.5k
Yandu Lu China 23 958 0.8× 1.2k 1.2× 185 0.7× 147 0.7× 207 1.3× 46 1.8k
Aliza Zarka Israel 23 1.2k 1.0× 1.7k 1.7× 186 0.8× 126 0.6× 299 1.9× 45 2.2k
Ying‐Fang Niu China 11 742 0.6× 780 0.8× 152 0.6× 158 0.7× 94 0.6× 19 1.1k
Audrey Beyly France 10 858 0.7× 838 0.8× 131 0.5× 140 0.7× 138 0.9× 11 1.2k
Eric R. Moellering United States 13 1.6k 1.4× 1.4k 1.4× 749 3.0× 179 0.8× 187 1.2× 15 2.2k
Kyle J. Lauersen Saudi Arabia 25 1.4k 1.2× 1.3k 1.3× 47 0.2× 154 0.7× 47 0.3× 57 2.0k
Oliver Kilian Germany 12 796 0.7× 517 0.5× 94 0.4× 77 0.4× 127 0.8× 13 1.1k
Xuemei Mao China 20 631 0.5× 1.1k 1.1× 130 0.5× 121 0.6× 133 0.8× 40 1.3k
J. Casey Lippmeier United States 12 826 0.7× 552 0.6× 104 0.4× 56 0.3× 164 1.0× 15 1.2k

Countries citing papers authored by Nanette Boyle

Since Specialization
Citations

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

Fields of papers citing papers by Nanette Boyle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nanette Boyle

This figure shows the co-authorship network connecting the top 25 collaborators of Nanette Boyle. A scholar is included among the top collaborators of Nanette Boyle 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 Nanette Boyle. Nanette Boyle 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.
Boyle, Nanette, et al.. (2025). Genome-scale metabolic models in cultivated meat: advances, challenges, and future directions. Current Opinion in Biotechnology. 94. 103313–103313. 1 indexed citations
2.
Boyle, Nanette, et al.. (2024). The phycosphere and its role in algal biofuel production. Frontiers in Climate. 6. 9 indexed citations
3.
Ramsey, Stephen A., et al.. (2024). Genome-scale metabolic model accurately predicts fermentation of glucose by Chromochloris zofingiensis. Algal Research. 84. 103805–103805. 2 indexed citations
4.
Huang, Weichao, Anagha Krishnan, Nicole Linka, et al.. (2023). Chlamydomonas mutants lacking chloroplast TRIOSE PHOSPHATE TRANSPORTER3 are metabolically compromised and light sensitive. The Plant Cell. 35(7). 2592–2614. 15 indexed citations
5.
Hodge, Bri‐Mathias, et al.. (2023). Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA. mSystems. 8(1). e0060120–e0060120. 2 indexed citations
6.
Boyle, Nanette, et al.. (2023). Systems biology and metabolic modeling for cultivated meat: A promising approach for cell culture media optimization and cost reduction. Comprehensive Reviews in Food Science and Food Safety. 22(4). 3422–3443. 23 indexed citations
7.
Kludze, Atsu, Devan Solanki, Rito Yanagi, et al.. (2022). Biocement from the ocean: Hybrid microbial-electrochemical mineralization of CO2. iScience. 25(10). 105156–105156. 7 indexed citations
8.
Hodge, Bri‐Mathias, et al.. (2019). Multiscale Multiobjective Systems Analysis (MiMoSA): an advanced metabolic modeling framework for complex systems. Scientific Reports. 9(1). 16948–16948. 11 indexed citations
9.
Boyle, Nanette, et al.. (2017). Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii. PLoS ONE. 12(5). e0177292–e0177292. 41 indexed citations
10.
11.
Boyle, Nanette, et al.. (2016). Omics in Chlamydomonas for Biofuel Production. Sub-cellular biochemistry. 86. 447–469. 12 indexed citations
12.
Zeitoun, Ramsey I., Andrew D. Garst, Gur Pines, et al.. (2015). Multiplexed tracking of combinatorial genomic mutations in engineered cell populations. Nature Biotechnology. 33(6). 631–637. 36 indexed citations
13.
Schmollinger, Stefan, Timo Mühlhaus, Nanette Boyle, et al.. (2014). Nitrogen-Sparing Mechanisms in Chlamydomonas Affect the Transcriptome, the Proteome, and Photosynthetic Metabolism. The Plant Cell. 26(4). 1410–1435. 272 indexed citations
14.
Boyle, Nanette, et al.. (2013). Genome-Wide Identification of Genes Conferring Energy Related Resistance to a Synthetic Antimicrobial Peptide (Bac8c). PLoS ONE. 8(1). e55052–e55052. 15 indexed citations
15.
Woodruff, Lauren B.A., Nanette Boyle, & Ryan T. Gill. (2013). Engineering improved ethanol production in Escherichia coli with a genome-wide approach. Metabolic Engineering. 17. 1–11. 39 indexed citations
16.
Blaby, Ian K., Anne Glaesener, Sorel Fitz‐Gibbon, et al.. (2013). Systems-Level Analysis of Nitrogen Starvation-Induced Modifications of Carbon Metabolism in a Chlamydomonas reinhardtii Starchless Mutant. The Plant Cell. 25(11). 4305–4323. 151 indexed citations
17.
Boyle, Nanette, M. Dudley Page, Bensheng Liu, et al.. (2012). Three Acyltransferases and Nitrogen-responsive Regulator Are Implicated in Nitrogen Starvation-induced Triacylglycerol Accumulation in Chlamydomonas. Journal of Biological Chemistry. 287(19). 15811–15825. 329 indexed citations
18.
Boyle, Nanette & Ryan T. Gill. (2012). Tools for genome-wide strain design and construction. Current Opinion in Biotechnology. 23(5). 666–671. 14 indexed citations
19.
Boyle, Nanette & John A. Morgan. (2011). Computation of metabolic fluxes and efficiencies for biological carbon dioxide fixation. Metabolic Engineering. 13(2). 150–158. 66 indexed citations
20.
Boyle, Nanette & John A. Morgan. (2009). Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Systems Biology. 3(1). 4–4. 331 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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