This map shows the geographic impact of J.J. Windig'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 J.J. Windig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.J. Windig more than expected).
This network shows the impact of papers produced by J.J. Windig. 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 J.J. Windig. The network helps show where J.J. Windig may publish in the future.
Co-authorship network of co-authors of J.J. Windig
This figure shows the co-authorship network connecting the top 25 collaborators of J.J. Windig.
A scholar is included among the top collaborators of J.J. Windig 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 J.J. Windig. J.J. Windig is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Doekes, Harmen P., R.F. Veerkamp, Piter Bijma, et al.. (2018). Genomic selection and inbreeding and kinship in Dutch-Flemish Holstein Friesian cattle. Socio-Environmental Systems Modeling. 90.4 indexed citations
7.
Schurink, Anouk, S. Eriksson, Mirte Bosse, et al.. (2018). Genetic diversity within and relationships among Dutch horse populations. Proceedings of the World Congress on Genetics Applied to Livestock Production. 268.1 indexed citations
Vandenplas, Jérémie, M.P.L. Calus, Claudia A. Sevillano, J.J. Windig, & J.W.M. Bastiaansen. (2016). Assigning breed origin to alleles in crossbred animals. Genetics Selection Evolution. 48(1). 61–61.41 indexed citations
10.
Calus, M.P.L., Hongli Huang, Yvonne C. J. Wientjes, et al.. (2014). (A)cross-breed Genomic Prediction. Socio-Environmental Systems Modeling. 1–6.2 indexed citations
11.
Bastiaansen, J.W.M., Marcos S. Lopes, B. Harlizius, et al.. (2014). Accuracy of Genomic Breeding Values Predicted Within and Across Breeds in Pig Populations. Socio-Environmental Systems Modeling.1 indexed citations
Urioste, J. I., Jessica Franzén, J.J. Windig, & E. Strandberg. (2011). Genetic Variability of Alternative Somatic Cell Count Traits and their Relationship with Clinical and Subclinical Mastitis. Socio-Environmental Systems Modeling. 44(44). 204–209.4 indexed citations
14.
Windig, J.J., A.H. Hoving-Bolink, & S.J. Hiemstra. (2010). Selection for scrapie resistance decreased inbreeding rates in two rare sheep breeds in the Netherlands. Socio-Environmental Systems Modeling. 200.1 indexed citations
15.
Windig, J.J., et al.. (2006). National and international perspectives in fangr conservation programmes. Socio-Environmental Systems Modeling.1 indexed citations
16.
Eaton, Deren A. R., et al.. (2006). Indicators to monitor livestock genetic diversity. Socio-Environmental Systems Modeling. 2006.1 indexed citations
17.
Beerda, B., W. Ouweltjes, J.J. Windig, M.P.L. Calus, & R.F. Veerkamp. (2005). Dairy cow health and the effects of genetic merit for milk production, management and interactions between these: blood metabolites and enzymes. Socio-Environmental Systems Modeling.2 indexed citations
18.
Windig, J.J., et al.. (1999). Evolutionary genetics of seasonal polyphenism in the map butterfly Araschnia levana (Nymphalidae: Lepidoptera). Evolutionary ecology research. 1(7). 875–894.21 indexed citations
Dyck, Hans Van, Erik Matthysen, J.J. Windig, & André A. Dhondt. (1997). Seasonal phenotypic variation in the speckled wood butterfly (Pararge aegeria L.): patterns in and relationships between wing characters. Belgian journal of zoology. 127(2). 167–178.2 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.