C. B. Williams

1.3k total citations
37 papers, 999 citations indexed

About

C. B. Williams is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, C. B. Williams has authored 37 papers receiving a total of 999 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Genetics, 19 papers in Agronomy and Crop Science and 16 papers in Animal Science and Zoology. Recurrent topics in C. B. Williams's work include Genetic and phenotypic traits in livestock (23 papers), Ruminant Nutrition and Digestive Physiology (16 papers) and Animal Nutrition and Physiology (10 papers). C. B. Williams is often cited by papers focused on Genetic and phenotypic traits in livestock (23 papers), Ruminant Nutrition and Digestive Physiology (16 papers) and Animal Nutrition and Physiology (10 papers). C. B. Williams collaborates with scholars based in United States, Spain and Netherlands. C. B. Williams's co-authors include T. G. Jenkins, Juan Manuel Falcón‐Pérez, Gary L. Bennett, Niels‐Christian Reichardt, Raquel Pazos, Félix Royo, J. W. Keele, Geert‐Jan Boons, Oier Aizpurua‐Olaizola and P.A. Oltenacu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Biometrics.

In The Last Decade

C. B. Williams

37 papers receiving 946 citations

Peers

C. B. Williams

ACS

GENET

ASZ

Louis Delbecchi Canada

Zhihua Ju China

Oliberto Sánchez Chile

W. M. Grosse United States

Jean‐Claude Twizere Belgium

M. L. Leite-Browning United States

Yutaka Sendai Japan

Linjun Hong China

Gregory W. Burns United States

Clara Slade Oliveira Brazil

Louis Delbecchi Canada

C. B. Williams

243 ×0.5

322 ×1.0

ACS

201 ×0.6

GENET

112 ×0.5

ASZ

150 ×0.8

Citations per year, relative to C. B. Williams C. B. Williams (= 1×) peers Louis Delbecchi

Countries citing papers authored by C. B. Williams

Since Specialization

Citations

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

Fields of papers citing papers by C. B. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. B. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of C. B. Williams. A scholar is included among the top collaborators of C. B. Williams 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 C. B. Williams. C. B. Williams 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

Gupta, Mainak Das, Frank Albrecht, Johannes Hemmerich, et al.. (2023). Scaling eukaryotic cell‐free protein synthesis achieved with the versatile and high‐yielding tobacco BY‐2 cell lysate. Biotechnology and Bioengineering. 120(10). 2890–2906. 27 indexed citations

Wilbers, Ruud H. P., et al.. (2023). Rapid screening and scaled manufacture of immunogenic virus-like particles in a tobacco BY-2 cell-free protein synthesis system. Frontiers in Immunology. 14. 1088852–1088852. 13 indexed citations

Williams, C. B., Raquel Pazos, Félix Royo, et al.. (2019). Assessing the role of surface glycans of extracellular vesicles on cellular uptake. Scientific Reports. 9(1). 11920–11920. 125 indexed citations

Magnabosco, C. de U., et al.. (2010). Selection for growth and maternal ability impacts simulation on the reproductive efficiency in a Nellore herd.. Revista Brasileira de Saúde e Produção Animal. 11(3). 641–650. 1 indexed citations

Williams, C. B. & Thomas G. Jenkins. (2006). Impact of selection for feed efficiency on beef life cycle performance.. 5 indexed citations

Williams, C. B., Gary L. Bennett, Thomas G. Jenkins, L. V. Cundiff, & C. L. Ferrell. (2006). Using simulation models to predict feed intake: Phenotypic and genetic relationships between observed and predicted values in cattle. Journal of Animal Science. 84(6). 1310–1316. 9 indexed citations

Williams, C. B.. (2005). Technical Note: A dynamic model to predict the composition of fat-free matter gains in cattle. Journal of Animal Science. 83(6). 1262–1266. 4 indexed citations

Williams, C. B. & T. G. Jenkins. (2003). A dynamic model of metabolizable energy utilization in growing and mature cattle. II. Metabolizable energy utilization for gain. Journal of Animal Science. 81(6). 1382–1389. 30 indexed citations

Williams, C. B. & T. G. Jenkins. (2003). A dynamic model of metabolizable energy utilization in growing and mature cattle. I. Metabolizable energy utilization for maintenance and support metabolism. Journal of Animal Science. 81(6). 1371–1381. 51 indexed citations

10.

Short, R. E., E. E. Grings, M. D. MacNeil, et al.. (1999). Effects of sire growth potential, growing-finishing strategy, and time on feed on performance, composition, and efficiency of steers.. Journal of Animal Science. 77(9). 2406–2406. 28 indexed citations

11.

Williams, C. B. & T. G. Jenkins. (1998). A computer model to predict composition of empty body weight changes in cattle at all stages of maturity.. Journal of Animal Science. 76(4). 980–980. 26 indexed citations

12.

Williams, C. B., Gary L. Bennett, & J. W. Keele. (1995). Simulated influence of postweaning production system on performance of different biological types of cattle: I. Estimation of model parameters. Journal of Animal Science. 73(3). 665–673. 13 indexed citations

13.

Williams, C. B. & Gary L. Bennett. (1995). Application of a computer model to predict optimum slaughter end points for different biological types of feeder cattle.. Journal of Animal Science. 73(10). 2903–2903. 19 indexed citations

14.

Williams, C. B., Gary L. Bennett, & J. W. Keele. (1995). Simulated influence of postweaning production system on performance of different biological types of cattle: III. Biological efficiency. Journal of Animal Science. 73(3). 686–698. 20 indexed citations

15.

Williams, C. B., Gary L. Bennett, & J. W. Keele. (1995). Simulated influence of postweaning production system on performance of different biological types of cattle: II. Carcass composition, retail product, and quality. Journal of Animal Science. 73(3). 674–685. 7 indexed citations

16.

Coleman, S. W., R. H. Gallavan, C. B. Williams, et al.. (1995). Silage or limit-fed grain growing diets for steers: I. Growth and carcass quality.. Journal of Animal Science. 73(9). 2609–2609. 30 indexed citations

17.

Bennett, Gary L. & C. B. Williams. (1994). Implications of genetic changes in body composition on beef production systems. Journal of Animal Science. 72(10). 2756–2763. 10 indexed citations

18.

Williams, C. B., J. W. Keele, & Gary L. Bennett. (1992). A computer model to predict the effects of level of nutrition on composition of empty body gain in beef cattle: II. Evaluation of the model1. Journal of Animal Science. 70(3). 858–866. 17 indexed citations

19.

Williams, C. B.. (1985). Correlation Analysis of Dairy Practices and Management Factors on New York Dairy Farms 1982. eCommons (Cornell University). 1 indexed citations

20.

Hughes, R., H. J. Olander, & C. B. Williams. (1975). Swine Dysentery: Pathogenicity of Treponema hyodysenteriae. American Journal of Veterinary Research. 36(7). 971–978. 43 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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