M.C.A.M. Bink

4.9k total citations
93 papers, 2.8k citations indexed

About

M.C.A.M. Bink is a scholar working on Genetics, Plant Science and Molecular Biology. According to data from OpenAlex, M.C.A.M. Bink has authored 93 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Genetics, 60 papers in Plant Science and 17 papers in Molecular Biology. Recurrent topics in M.C.A.M. Bink's work include Genetic Mapping and Diversity in Plants and Animals (60 papers), Genetic and phenotypic traits in livestock (47 papers) and Genetics and Plant Breeding (23 papers). M.C.A.M. Bink is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (60 papers), Genetic and phenotypic traits in livestock (47 papers) and Genetics and Plant Breeding (23 papers). M.C.A.M. Bink collaborates with scholars based in Netherlands, United States and France. M.C.A.M. Bink's co-authors include Eric van de Weg, Fred A. van Eeuwijk, Cajo J. F. ter Braak, Satish Kumar, David Chagné, Richard K. Volz, Roeland E. Voorrips, Martin P. Boer, M.P.L. Calus and Ritsert C. Jansen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.

In The Last Decade

M.C.A.M. Bink

90 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M.C.A.M. Bink Netherlands 32 2.0k 1.4k 774 276 136 93 2.8k
Weiming He China 16 1.7k 0.8× 1.2k 0.9× 853 1.1× 86 0.3× 176 1.3× 54 2.9k
Brigitte Mangin France 29 2.3k 1.1× 1.6k 1.2× 503 0.6× 96 0.3× 113 0.8× 60 3.0k
I. Vroh Bi Belgium 10 3.1k 1.5× 2.6k 1.9× 797 1.0× 111 0.4× 122 0.9× 14 4.2k
Vincent Segura France 22 1.9k 0.9× 1.1k 0.8× 794 1.0× 80 0.3× 105 0.8× 54 2.7k
Gaël Pressoir United States 11 3.5k 1.7× 2.9k 2.1× 699 0.9× 118 0.4× 125 0.9× 16 4.6k
Masanori Yamasaki Japan 21 4.4k 2.1× 3.6k 2.6× 1.0k 1.3× 135 0.5× 206 1.5× 62 5.7k
Yidan Ouyang China 30 2.9k 1.4× 1.5k 1.1× 1.7k 2.2× 73 0.3× 140 1.0× 79 3.6k
Alain Ghesquière France 32 2.4k 1.2× 700 0.5× 728 0.9× 82 0.3× 61 0.4× 64 2.6k
Zhengqiang Ma China 36 3.8k 1.8× 870 0.6× 732 0.9× 1.0k 3.6× 66 0.5× 111 4.0k
Alexander Kozik United States 23 2.9k 1.4× 585 0.4× 1.4k 1.8× 195 0.7× 229 1.7× 36 3.6k

Countries citing papers authored by M.C.A.M. Bink

Since Specialization
Citations

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

Fields of papers citing papers by M.C.A.M. Bink

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.C.A.M. Bink. 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 M.C.A.M. Bink. The network helps show where M.C.A.M. Bink may publish in the future.

Co-authorship network of co-authors of M.C.A.M. Bink

This figure shows the co-authorship network connecting the top 25 collaborators of M.C.A.M. Bink. A scholar is included among the top collaborators of M.C.A.M. Bink 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 M.C.A.M. Bink. M.C.A.M. Bink 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.
Bink, M.C.A.M., et al.. (2023). Genome‐wide association studies for additive and dominance effects for body composition traits in commercial crossbred Piétrain pigs. Journal of Animal Breeding and Genetics. 140(4). 413–430. 10 indexed citations
2.
Perez, B.C., M.C.A.M. Bink, Karen L. Svenson, Gary A. Churchill, & M.P.L. Calus. (2022). Prediction performance of linear models and gradient boosting machine on complex phenotypes in outbred mice. G3 Genes Genomes Genetics. 12(4). 14 indexed citations
3.
Perez, B.C., M.C.A.M. Bink, Karen L. Svenson, Gary A. Churchill, & M.P.L. Calus. (2022). Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence. G3 Genes Genomes Genetics. 12(11). 7 indexed citations
4.
Crespo‐Piazuelo, Daniel, Hervé Acloque, Olga González-Rodríguez, et al.. (2022). Identification of transcriptional regulatory variants in pig duodenum, liver, and muscle tissues. GigaScience. 12. 10 indexed citations
5.
Derks, Martijn F. L., Benjamin J. Wood, R.P.M.A. Crooijmans, et al.. (2022). A new haplotype-resolved turkey genome to enable turkey genetics and genomics research. GigaScience. 12. 7 indexed citations
6.
Laenen, Benjamin, Andrew Tedder, Michael Nowak, et al.. (2018). Demography and mating system shape the genome-wide impact of purifying selection in Arabis alpina. Proceedings of the National Academy of Sciences. 115(4). 816–821. 54 indexed citations
7.
Durand, Jean-Baptiste, et al.. (2017). Genetic determinism of flowering regularity over years in an apple multi-family population. HAL (Le Centre pour la Communication Scientifique Directe).
8.
Bink, M.C.A.M., Sébastien Martinez, Jean‐Jacques Kelner, et al.. (2016). Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population. Journal of Experimental Botany. 67(9). 2875–2888. 76 indexed citations
9.
Voorrips, Roeland E., et al.. (2016). PediHaplotyper: software for consistent assignment of marker haplotypes in pedigrees. Molecular Breeding. 36(8). 119–119. 39 indexed citations
10.
Weg, Eric van de, M.C.A.M. Bink, Roeland E. Voorrips, et al.. (2015). Pedigree based analyses: a powerful approach for QTL discovery in pedigreed breeding germplasm and support on breeding decisions. Socio-Environmental Systems Modeling. 14(2). 12–19. 1 indexed citations
11.
Muranty, Hélène, Michela Troggio, Inès Ben Sadok, et al.. (2015). Accuracy and responses of genomic selection on key traits in apple breeding. Horticulture Research. 2(1). 15060–15060. 101 indexed citations
12.
Binsbergen, R. van, M.P.L. Calus, M.C.A.M. Bink, et al.. (2014). Genomic Prediction with 12.5 Million SNPs for 5503 Holstein Friesian Bulls. Socio-Environmental Systems Modeling. 664. 2 indexed citations
13.
Kumar, Satish, Dorian J. Garrick, M.C.A.M. Bink, et al.. (2013). Novel genomic approaches unravel genetic architecture of complex traits in apple. BMC Genomics. 14(1). 393–393. 97 indexed citations
14.
Bastiaansen, J.W.M., et al.. (2010). QTLMAS 2009: simulated dataset. BMC Proceedings. 4(S1). S3–S3. 18 indexed citations
15.
Maliepaard, Chris, et al.. (2010). Comparison of analyses of the QTLMAS XIII common dataset. II: QTL analysis. BMC Proceedings. 4(S1). S2–S2. 1 indexed citations
16.
Kourmpetis, Yiannis, Aalt D. J. van Dijk, M.C.A.M. Bink, Roeland C. H. J. van Ham, & Cajo J. F. ter Braak. (2010). Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data. PLoS ONE. 5(2). e9293–e9293. 70 indexed citations
17.
Malosetti, Marcos, Martin P. Boer, M.C.A.M. Bink, & Fred A. van Eeuwijk. (2006). Multi-trait QTL analysis based on mixed models with parsimonious covariance matrices. Socio-Environmental Systems Modeling. 8 indexed citations
18.
Bink, M.C.A.M.. (2002). On flexible finite polygenic models for multiple-trait evaluation. Genetics Research. 80(3). 245–256. 13 indexed citations
19.
Bink, M.C.A.M., et al.. (1998). Bayesian estimation of dispersion parameters with a reduced animal model including polygenic and QTL effects. Genetics Selection Evolution. 30(2). 16 indexed citations
20.
Bink, M.C.A.M., et al.. (1998). Bayesian estimation of dispersion parameters with a reduced animal model including polygenic and QTL effects. Genetics Selection Evolution. 30(2). 103–125. 6 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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