Deborah Wilson

1.7k total citations
54 papers, 1.2k citations indexed

About

Deborah Wilson is a scholar working on Genetics, Animal Science and Zoology and Agronomy and Crop Science. According to data from OpenAlex, Deborah Wilson has authored 54 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Genetics, 31 papers in Animal Science and Zoology and 15 papers in Agronomy and Crop Science. Recurrent topics in Deborah Wilson's work include Genetic and phenotypic traits in livestock (40 papers), Effects of Environmental Stressors on Livestock (21 papers) and Meat and Animal Product Quality (21 papers). Deborah Wilson is often cited by papers focused on Genetic and phenotypic traits in livestock (40 papers), Effects of Environmental Stressors on Livestock (21 papers) and Meat and Animal Product Quality (21 papers). Deborah Wilson collaborates with scholars based in United States, Canada and Australia. Deborah Wilson's co-authors include Gene H. Rouse, R. L. Willham, S. L. Northcutt, Abebe T. Hassen, L. V. Cundiff, Scott Patrick Greiner, T. L. Wheeler, Jennifer M Bormann, Viren Amin and Richard G. Tait and has published in prestigious journals such as Energy, Journal of Animal Science and International Journal of Medical Informatics.

In The Last Decade

Deborah Wilson

51 papers receiving 1.1k citations

Peers

Deborah Wilson

GENET

ASZ

ACS

S. Korver Netherlands

J. Přibyl Czechia

Jarmo Juga Finland

R. T. BERG Canada

José Braccini Neto Brazil

B.D. Valente United States

Susanne Stern Sweden

Clara Díaz Spain

M. J. Drennan Ireland

A. L. Rae New Zealand

S. Korver Netherlands

Deborah Wilson

810 ×1.1

GENET

294 ×0.5

ASZ

664 ×1.8

ACS

102 ×0.6

89 ×1.2

Citations per year, relative to Deborah Wilson Deborah Wilson (= 1×) peers S. Korver

Countries citing papers authored by Deborah Wilson

Since Specialization

Citations

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

Fields of papers citing papers by Deborah Wilson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deborah Wilson

This figure shows the co-authorship network connecting the top 25 collaborators of Deborah Wilson. A scholar is included among the top collaborators of Deborah Wilson 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 Deborah Wilson. Deborah Wilson 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

Bormann, Jennifer M & Deborah Wilson. (2010). Calving day and age at first calving in Angus heifers1. Journal of Animal Science. 88(6). 1947–1956. 43 indexed citations

Tait, Richard G., Deborah Wilson, & Gene H. Rouse. (2005). Prediction of retail product and trimmable fat yields from the four primal cuts in beef cattle using ultrasound or carcass data1. Journal of Animal Science. 83(6). 1353–1360. 39 indexed citations

Hassen, Abebe T., Deborah Wilson, Gene H. Rouse, & Richard G. Tait. (2004). Partitioning variances of growth in ultrasound longissimus muscle area measures in Angus bulls and heifers1. Journal of Animal Science. 82(5). 1272–1279. 11 indexed citations

Bullock, Kim, et al.. (2003). International beef cattle genetic evaluation in the United States and the role of the National Beef Cattle Evaluation Consortium. Bulletin - International Bull Evaluation Service/Interbull bulletin. 156. 1 indexed citations

Greiner, Scott Patrick, Gene H. Rouse, Deborah Wilson, L. V. Cundiff, & T. L. Wheeler. (2003). The relationship between ultrasound measurements and carcass fat thickness and longissimus muscle area in beef cattle. Journal of Animal Science. 81(3). 676–682. 84 indexed citations

Greiner, Scott Patrick, Gene H. Rouse, Deborah Wilson, L. V. Cundiff, & T. L. Wheeler. (2003). Prediction of retail product weight and percentage using ultrasound and carcass measurements in beef cattle. Journal of Animal Science. 81(7). 1736–1742. 58 indexed citations

Rouse, Gene H., Deborah Wilson, & Abebe T. Hassen. (2002). Body Composition Changes of Angus Females from Initial Breeding through Second Parturition and Weaning Determined by Real-time Ultrasound. Iowa State University Digital Repository (Iowa State University). 1(1). 1 indexed citations

Sapp, R. L., J. K. Bertrand, T. D. Pringle, & Deborah Wilson. (2002). Effects of selection for ultrasound intramuscular fat percentage in Angus bulls on carcass traits of progeny. Journal of Animal Science. 80(8). 2017–2017. 34 indexed citations

Hassen, Abebe T., et al.. (2001). Predicting percentage of intramuscular fat using two types of real-time ultrasound equipment.. Journal of Animal Science. 79(1). 11–11. 56 indexed citations

10.

Wilson, Deborah, et al.. (2000). Genetic Evaluation for Birth Weight and First-Calf Calving Ease for the Angus Breed. Iowa State University Digital Repository (Iowa State University). 1(1). 1 indexed citations

11.

Wilson, Deborah, et al.. (1999). Prediction of Carcass Traits Using Live Animal Ultrasound. Iowa State University Digital Repository (Iowa State University). 1(1). 14 indexed citations

12.

Hassen, Abebe T., Deborah Wilson, Viren Amin, & Gene H. Rouse. (1999). Repeatability of ultrasound-predicted percentage of intramuscular fat in feedlot cattle.. Journal of Animal Science. 77(6). 1335–1335. 25 indexed citations

13.

Hoffman, M. P., et al.. (1998). Using Real-Time Ultrasound During the Feeding Period to Predict Cattle Composition.. Iowa State University Digital Repository (Iowa State University). 1(1). 2 indexed citations

14.

Lau, Francis, et al.. (1998). The diffusion of an evidence-based disease guidance system for managing stroke. International Journal of Medical Informatics. 51(2-3). 107–116. 12 indexed citations

15.

Amin, Viren, et al.. (1997). Application of Newer Signal and Image-Processing Techniques for Ultrasound Beef Quality Evaluation Research. Iowa State University Digital Repository (Iowa State University). 1(1). 1 indexed citations

16.

Amin, Viren, et al.. (1997). Application of Statistical Methods for Improving Models of Intramuscular Percentage Fat Prediction in Live Beef Animals From Real-Time Ultrasound Images. Iowa State University Digital Repository (Iowa State University). 1(1). 2 indexed citations

17.

Northcutt, S. L., Deborah Wilson, & J.A. Hoekstra. (1994). Effect of positive genetic trend for mature size on age-of-dam adjustment factors for weaning weight in Angus field records. Journal of Animal Science. 72(4). 828–832. 5 indexed citations

18.

Northcutt, S. L., Deborah Wilson, & R. L. Willham. (1992). Adjusting weight for body condition score in Angus cows. Journal of Animal Science. 70(5). 1342–1345. 31 indexed citations

19.

Wilson, Deborah. (1992). Application of ultrasound for genetic improvement. Journal of Animal Science. 70(3). 973–983. 92 indexed citations

20.

Hertzler, Greg, Deborah Wilson, Daniel D. Loy, & Gene H. Rouse. (1988). Optimal Beef Cattle Diets Formulated by Nonlinear Programming. Journal of Animal Science. 66(5). 1115–1115. 5 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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