Joanne C. Cusumano

2.0k total citations
17 papers, 1.6k citations indexed

About

Joanne C. Cusumano is a scholar working on Molecular Biology, Biotechnology and Animal Science and Zoology. According to data from OpenAlex, Joanne C. Cusumano has authored 17 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Biotechnology and 3 papers in Animal Science and Zoology. Recurrent topics in Joanne C. Cusumano's work include Plant Gene Expression Analysis (9 papers), Biochemical and biochemical processes (5 papers) and Plant biochemistry and biosynthesis (4 papers). Joanne C. Cusumano is often cited by papers focused on Plant Gene Expression Analysis (9 papers), Biochemical and biochemical processes (5 papers) and Plant biochemistry and biosynthesis (4 papers). Joanne C. Cusumano collaborates with scholars based in United States and Germany. Joanne C. Cusumano's co-authors include Clint Chapple, Knut Meyer, Amber M. Shirley, Max O. Ruegger, Rochus Franke, Christopher R. Somerville, Colleen M. McMichael, Matthew R. Hemm, John M. Humphreys and Jeff W. Denault and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Plant Cell and PLANT PHYSIOLOGY.

In The Last Decade

Joanne C. Cusumano

17 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joanne C. Cusumano United States 14 1.2k 664 520 342 93 17 1.6k
J. H. Bryce United Kingdom 21 721 0.6× 814 1.2× 184 0.4× 123 0.4× 51 0.5× 66 1.4k
Francisca Rández‐Gil Spain 25 1.6k 1.3× 470 0.7× 431 0.8× 182 0.5× 86 0.9× 63 2.0k
Yuya Kumagai Japan 23 805 0.7× 259 0.4× 245 0.5× 427 1.2× 52 0.6× 73 1.4k
Howard G. Damude United States 15 816 0.7× 922 1.4× 331 0.6× 219 0.6× 11 0.1× 18 1.6k
Tony D’Amore Canada 20 917 0.7× 222 0.3× 512 1.0× 138 0.4× 67 0.7× 41 1.3k
Meiru Li China 24 1.3k 1.1× 1.5k 2.2× 97 0.2× 107 0.3× 26 0.3× 70 2.0k
Emilia Matallana Spain 23 1.1k 0.9× 383 0.6× 197 0.4× 131 0.4× 63 0.7× 69 1.5k
Shodo Hara Japan 21 1.1k 0.9× 351 0.5× 440 0.8× 536 1.6× 27 0.3× 82 1.5k
Charles D. Boyer United States 28 421 0.3× 1.4k 2.1× 526 1.0× 357 1.0× 16 0.2× 69 2.3k
Antoni Banaś Poland 23 1.9k 1.5× 1.1k 1.6× 295 0.6× 37 0.1× 16 0.2× 62 2.8k

Countries citing papers authored by Joanne C. Cusumano

Since Specialization
Citations

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

Fields of papers citing papers by Joanne C. Cusumano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joanne C. Cusumano. 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 Joanne C. Cusumano. The network helps show where Joanne C. Cusumano may publish in the future.

Co-authorship network of co-authors of Joanne C. Cusumano

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

All Works

17 of 17 papers shown
1.
2.
Liu, Jiliang, Jeongim Kim, Joanne C. Cusumano, et al.. (2016). The impact of alterations in lignin deposition on cellulose organization of the plant cell wall. Biotechnology for Biofuels. 9(1). 126–126. 32 indexed citations
3.
Liu, Jiliang, Hideyo Inouye, Nagarajan Venugopalan, et al.. (2013). Tissue specific specialization of the nanoscale architecture of Arabidopsis. Journal of Structural Biology. 184(2). 103–114. 13 indexed citations
4.
Franke, Rochus, John M. Humphreys, Matthew R. Hemm, et al.. (2002). The ArabidopsisREF8 gene encodes the 3‐hydroxylase of phenylpropanoid metabolism. The Plant Journal. 30(1). 33–45. 237 indexed citations
5.
Franke, Rochus, Colleen M. McMichael, Knut Meyer, et al.. (2000). Modified lignin in tobacco and poplar plants over‐expressing the Arabidopsis gene encoding ferulate 5‐hydroxylase. The Plant Journal. 22(3). 223–234. 239 indexed citations
6.
Shirley, Amber M., Knut Andreas Meyer, Max O. Ruegger, et al.. (2000). Cloning of the SNG1 Gene of Arabidopsis Reveals a Role for a Serine Carboxypeptidase-Like Protein as an Acyltransferase in Secondary Metabolism. The Plant Cell. 12(8). 1295–1295. 11 indexed citations
7.
Shirley, Amber M., Knut Meyer, Max O. Ruegger, et al.. (2000). Cloning of the SNG1 Gene of Arabidopsis Reveals a Role for a Serine Carboxypeptidase-like Protein as an Acyltransferase in Secondary Metabolism. The Plant Cell. 12(8). 1295–1306. 185 indexed citations
8.
Ruegger, Max O., Knut Meyer, Joanne C. Cusumano, & Clint Chapple. (1999). Regulation of Ferulate-5-Hydroxylase Expression in Arabidopsis in the Context of Sinapate Ester Biosynthesis1. PLANT PHYSIOLOGY. 119(1). 101–110. 93 indexed citations
9.
Meyer, Knut, et al.. (1998). Lignin monomer composition is determined by the expression of a cytochrome P450-dependent monooxygenase in Arabidopsis. Proceedings of the National Academy of Sciences. 95(12). 6619–6623. 272 indexed citations
10.
Cusumano, Joanne C., et al.. (1997). Regulation in Response to Development and the Environment. 14 indexed citations
11.
Cusumano, Joanne C., et al.. (1997). Cinnamate-4-Hydroxylase Expression in Arabidopsis (Regulation in Response to Development and the Environment). PLANT PHYSIOLOGY. 113(3). 729–738. 189 indexed citations
12.
Meyer, Knut, Joanne C. Cusumano, Christopher R. Somerville, & Clint Chapple. (1996). Ferulate-5-hydroxylase from Arabidopsis thaliana defines a new family of cytochrome P450-dependent monooxygenases.. Proceedings of the National Academy of Sciences. 93(14). 6869–6874. 164 indexed citations
13.
Spurlock, Michael E., Joanne C. Cusumano, Shaoquan Ji, et al.. (1994). The effect of ractopamine on β-adrenoceptor density and affinity in porcine adipose and skeletal muscle tissue. Journal of Animal Science. 72(1). 75–80. 61 indexed citations
14.
Spurlock, Michael E., Joanne C. Cusumano, & S. E. Mills. (1993). The affinity of ractopamine, clenbuterol, and L-644,969 for the β-adrenergic receptor population in porcine adipose tissue and skeletal muscle membrane. Journal of Animal Science. 71(8). 2061–2065. 25 indexed citations
15.
Spurlock, Michael E., Joanne C. Cusumano, & S. E. Mills. (1993). (-)-[3H]-dihydroalprenolol binding to β-adrenergic receptors in porcine adipose tissue and skeletal muscle membrane preparations. Journal of Animal Science. 71(7). 1778–1785. 16 indexed citations
16.
Smith, Jean B., Joanne C. Cusumano, & Charles F. Babbs. (1990). Quantitative Effects of Iron Chelators on Hydroxyl Radical Production by the Superoxide-Driven Fenton Reaction. Free Radical Research Communications. 8(2). 101–106. 40 indexed citations
17.
Smith, Jean B., Joanne C. Cusumano, & Charles F. Babbs. (1989). Quantitative Effects of Iron Chelators on Hydroxyl Radical Production by the Superoxide-Driven Fenton Raction. Purdue e-Pubs (Purdue University System). 9 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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