Daniel J. Skylas

1.0k total citations
28 papers, 723 citations indexed

About

Daniel J. Skylas is a scholar working on Plant Science, Food Science and Nutrition and Dietetics. According to data from OpenAlex, Daniel J. Skylas has authored 28 papers receiving a total of 723 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Plant Science, 12 papers in Food Science and 11 papers in Nutrition and Dietetics. Recurrent topics in Daniel J. Skylas's work include Food composition and properties (11 papers), Phytase and its Applications (11 papers) and Proteins in Food Systems (10 papers). Daniel J. Skylas is often cited by papers focused on Food composition and properties (11 papers), Phytase and its Applications (11 papers) and Proteins in Food Systems (10 papers). Daniel J. Skylas collaborates with scholars based in Australia, Japan and United Kingdom. Daniel J. Skylas's co-authors include C.W. Wrigley, Les Copeland, W.G. Rathmell, Stuart J. Cordwell, David J. Basseal, Bradley J. Walsh, Caron Blumenthal, Ken Quail, Joel B. Johnson and Mani Naiker and has published in prestigious journals such as Molecules, PROTEOMICS and Journal of Cereal Science.

In The Last Decade

Daniel J. Skylas

27 papers receiving 693 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Skylas Australia 16 456 180 161 155 59 28 723
John Gorham United Kingdom 19 673 1.5× 192 1.1× 186 1.2× 230 1.5× 70 1.2× 27 984
Steven P. Swanson United States 18 588 1.3× 148 0.8× 129 0.8× 12 0.1× 48 0.8× 37 932
Jinyu Li China 15 486 1.1× 256 1.4× 78 0.5× 45 0.3× 17 0.3× 33 692
Friedrich J. Zeller Germany 24 1.1k 2.5× 187 1.0× 102 0.6× 115 0.7× 73 1.2× 50 1.3k
Sihua Cheng China 17 359 0.8× 397 2.2× 321 2.0× 21 0.1× 9 0.2× 18 956
Francesca Debegnach Italy 20 986 2.2× 143 0.8× 287 1.8× 22 0.1× 10 0.2× 38 1.1k
Donatella Resta Italy 14 204 0.4× 267 1.5× 202 1.3× 139 0.9× 12 0.2× 18 710
Monique de Nijs Netherlands 21 656 1.4× 179 1.0× 277 1.7× 30 0.2× 12 0.2× 37 1.1k
Lu‐Lu Zhang China 13 202 0.4× 192 1.1× 155 1.0× 31 0.2× 7 0.1× 45 583
Masatoshi Tanida Japan 13 570 1.3× 347 1.9× 31 0.2× 140 0.9× 16 0.3× 27 811

Countries citing papers authored by Daniel J. Skylas

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Skylas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Skylas. 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 Daniel J. Skylas. The network helps show where Daniel J. Skylas may publish in the future.

Co-authorship network of co-authors of Daniel J. Skylas

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Skylas. A scholar is included among the top collaborators of Daniel J. Skylas 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 Daniel J. Skylas. Daniel J. Skylas 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.
Messina, Valeria, Daniel J. Skylas, Thomas H. Roberts, et al.. (2025). Pulse Proteins: Processing, Nutrition, and Functionality in Foods. Foods. 14(7). 1151–1151. 8 indexed citations
2.
Skylas, Daniel J., et al.. (2025). Improving the Nutritional Quality of Instant Noodles Made From Wheat Flour Using Dry and Wet Fractionated Mungbean Protein Ingredients. Cereal Chemistry. 102(3). 520–536. 1 indexed citations
3.
Hopf, Andreas, et al.. (2024). Techno‐Functional Properties of Dry and Wet Fractionated Pulse Protein Ingredients. Legume Science. 6(4). 7 indexed citations
4.
Messina, Valeria, Daniel J. Skylas, Peter Valtchev, et al.. (2024). Effect of Dry and Wet Fractionation on Nutritional and Physicochemical Properties of Faba Bean and Yellow Pea Protein. Legume Science. 6(2). 12 indexed citations
5.
Skylas, Daniel J., et al.. (2024). Dry fractionation of Australian mungbean for sustainable production of value‐added protein concentrate ingredients. Cereal Chemistry. 101(4). 720–738. 6 indexed citations
7.
Johnson, Joel B., Daniel J. Skylas, Janice S. Mani, et al.. (2021). Phenolic Profiles of Ten Australian Faba Bean Varieties. Molecules. 26(15). 4642–4642. 26 indexed citations
8.
Johnson, Joel B., et al.. (2020). Profiling the varietal antioxidative contents and macrochemical composition in Australian faba beans (Vicia faba L.). Legume Science. 2(2). 34 indexed citations
9.
Skylas, Daniel J., Mark P. Molloy, Robert D. Willows, Christopher Blanchard, & Ken Quail. (2017). Characterisation of Protein Isolates Prepared from Processed Mungbean (Vigna radiata) Flours. Journal of Agricultural Science. 9(12). 1–1. 5 indexed citations
10.
Skylas, Daniel J., Christopher Blanchard, & Ken Quail. (2017). Variation in Nutritional Composition of Australian Mungbean Varieties. Journal of Agricultural Science. 9(5). 45–45. 15 indexed citations
11.
Wu, Ming, Thomas Giersch, Stephen McKay, et al.. (2011). A novel hardness-related and starch granule-associated protein marker in wheat: LMW-GS-‘S’. Journal of Cereal Science. 55(2). 153–159. 3 indexed citations
12.
Skylas, Daniel J., Robert D. Willows, Angela Connolly, et al.. (2006). A proteomic approach to the identification and characterisation of protein composition in wheat germ. Functional & Integrative Genomics. 6(4). 322–337. 29 indexed citations
13.
Skylas, Daniel J., Stuart J. Cordwell, George E. Craft, et al.. (2005). Proteome analysis of two soft-grained wheats of different processing quality: cultivar-specific proteins. Australian Journal of Agricultural Research. 56(2). 145–155. 6 indexed citations
14.
Skylas, Daniel J., Dewald van Dyk, & C.W. Wrigley. (2004). Proteomics of wheat grain. Journal of Cereal Science. 41(2). 165–179. 49 indexed citations
15.
Skylas, Daniel J., Stuart J. Cordwell, Peter G. Hains, et al.. (2002). Heat Shock of Wheat During Grain Filling: Proteins Associated with Heat-tolerance. Journal of Cereal Science. 35(2). 175–188. 105 indexed citations
16.
Skylas, Daniel J., Les Copeland, W.G. Rathmell, & C.W. Wrigley. (2001). The wheat-grain proteome as a basis for more efficient cultivar identification. PROTEOMICS. 1(12). 1542–1542. 38 indexed citations
17.
Littlejohn, Tamantha K., Osamu Takikawa, Daniel J. Skylas, et al.. (2000). Expression and Purification of Recombinant Human Indoleamine 2,3-Dioxygenase. Protein Expression and Purification. 19(1). 22–29. 66 indexed citations
18.
Clarke, B. C., Matthew Hobbs, Daniel J. Skylas, & R. Appels. (2000). Genes active in developing wheat endosperm. Functional & Integrative Genomics. 1(1). 44–55. 44 indexed citations
19.
Clarke, B. C., et al.. (2000). Genes active in developing wheat endosperm. Functional & Integrative Genomics. 1(1). 44–44. 24 indexed citations
20.
Skylas, Daniel J., James A. Mackintosh, Stuart J. Cordwell, et al.. (2000). Proteome Approach to the Characterisation of Protein Composition in the Developing and Mature Wheat-grain Endosperm. Journal of Cereal Science. 32(2). 169–188. 105 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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