M.F.W. te Pas

3.4k total citations
104 papers, 2.5k citations indexed

About

M.F.W. te Pas is a scholar working on Molecular Biology, Genetics and Animal Science and Zoology. According to data from OpenAlex, M.F.W. te Pas has authored 104 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 40 papers in Genetics and 29 papers in Animal Science and Zoology. Recurrent topics in M.F.W. te Pas's work include Genetic and phenotypic traits in livestock (27 papers), Meat and Animal Product Quality (19 papers) and Muscle Physiology and Disorders (17 papers). M.F.W. te Pas is often cited by papers focused on Genetic and phenotypic traits in livestock (27 papers), Meat and Animal Product Quality (19 papers) and Muscle Physiology and Disorders (17 papers). M.F.W. te Pas collaborates with scholars based in Netherlands, China and France. M.F.W. te Pas's co-authors include S.C. Liefers, T. van der Lende, R.F. Veerkamp, G. Rettenberger, Carole Delavaud, Yves Chilliard, R.F. Veerkamp, A. Soumillion, Frans Gerbens and Johannes A. Lenstra and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

M.F.W. te Pas

101 papers receiving 2.3k 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.F.W. te Pas Netherlands 29 1.1k 914 865 366 283 104 2.5k
C. Óvilo Spain 32 1.6k 1.5× 1.1k 1.2× 816 0.9× 542 1.5× 173 0.6× 134 3.1k
Christopher M. Ashwell United States 31 796 0.7× 1.5k 1.6× 585 0.7× 193 0.5× 317 1.1× 77 2.6k
Ana I. Fernández Spain 29 1.6k 1.4× 698 0.8× 868 1.0× 314 0.9× 81 0.3× 103 2.7k
Nadine Buys Belgium 31 1.7k 1.5× 1.4k 1.5× 757 0.9× 230 0.6× 72 0.3× 152 3.5k
Florence Gondret France 32 780 0.7× 1.9k 2.1× 1.1k 1.2× 1000 2.7× 69 0.2× 109 3.7k
J. Estany Spain 30 977 0.9× 1.6k 1.7× 320 0.4× 219 0.6× 93 0.3× 114 2.4k
Ramona N. Pena Spain 24 1.0k 0.9× 751 0.8× 620 0.7× 247 0.7× 44 0.2× 106 1.8k
Theodore H. Elsasser United States 29 412 0.4× 764 0.8× 637 0.7× 246 0.7× 93 0.3× 96 2.7k
R. Davoli Italy 34 1.7k 1.5× 1.3k 1.5× 942 1.1× 299 0.8× 34 0.1× 144 3.0k
M. Schwerin Germany 35 2.2k 2.0× 464 0.5× 1.1k 1.3× 279 0.8× 46 0.2× 156 3.5k

Countries citing papers authored by M.F.W. te Pas

Since Specialization
Citations

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

Fields of papers citing papers by M.F.W. te Pas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.F.W. te Pas. 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.F.W. te Pas. The network helps show where M.F.W. te Pas may publish in the future.

Co-authorship network of co-authors of M.F.W. te Pas

This figure shows the co-authorship network connecting the top 25 collaborators of M.F.W. te Pas. A scholar is included among the top collaborators of M.F.W. te Pas 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.F.W. te Pas. M.F.W. te Pas 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.
Schokker, Dirkjan, Alex Bossers, M.F.W. te Pas, et al.. (2023). Dietary strategies can increase cloacal endotoxin levels and modulate the resident microbiota in broiler chickens. Poultry Science. 103(2). 103312–103312. 3 indexed citations
2.
Kim, Sang-Wook, Seung-Chai Kim, M.F.W. te Pas, et al.. (2020). Integrated time-serial transcriptome networks reveal common innate and tissue-specific adaptive immune responses to PRRSV infection. Veterinary Research. 51(1). 128–128. 23 indexed citations
3.
Kim, Jun‐Mo, Jong‐Eun Park, Inkyu Yoo, et al.. (2018). Integrated transcriptomes throughout swine oestrous cycle reveal dynamic changes in reproductive tissues interacting networks. Scientific Reports. 8(1). 5436–5436. 33 indexed citations
4.
Pas, M.F.W. te, Woncheoul Park, Krishnamoorthy Srikanth, et al.. (2018). Transcriptomic profiles of muscle, heart, and spleen in reaction to circadian heat stress in Ethiopian highland and lowland male chicken. Cell Stress and Chaperones. 24(1). 175–194. 10 indexed citations
5.
Butler, S.T., et al.. (2017). Validation of a mathematical model of the bovine estrous cycle for cows with different estrous cycle characteristics. animal. 11(11). 1991–2001. 6 indexed citations
6.
Woelders, H., et al.. (2014). Central genomic regulation of the expression of oestrous behaviour in dairy cows: a review. animal. 8(5). 754–764. 16 indexed citations
7.
Kommadath, Arun, M.F.W. te Pas, & M.A. Smits. (2013). Gene coexpression network analysis identifies genes and biological processes shared among anterior pituitary and brain areas that affect estrous behavior in dairy cows. Journal of Dairy Science. 96(4). 2583–2595. 12 indexed citations
8.
Pas, M.F.W. te, et al.. (2012). Developing biomarkers to improve, detect and monitor high pork quality. 65–81.
9.
Marcos, Begonya, P. Gou, María Dolors Guárdia, et al.. (2012). Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry: A tool to predict pork quality. Meat Science. 95(3). 688–693. 7 indexed citations
10.
Marcos, Begonya, P. Gou, X. Serra, et al.. (2012). Analysis of raw hams using SELDI-TOF-MS to predict the final quality of dry-cured hams. Meat Science. 93(2). 233–239. 4 indexed citations
11.
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13.
Liefers, S.C., R.F. Veerkamp, M.F.W. te Pas, et al.. (2005). Leptin promoter mutations affect leptin levels and performance traits in dairy cows1. Animal Genetics. 36(2). 111–118. 60 indexed citations
14.
Pas, M.F.W. te. (2004). Candidate genes for meat production and meat quality - the MRF genes. Animal Science Papers and Reports. 22(1). 115–118. 13 indexed citations
15.
Yu, Mei, M.F.W. te Pas, M. Yerle, et al.. (2004). Sequence characterization, polymorphism and chromosomal localizations of the porcine PSME1 and PSME2 genes1. Animal Genetics. 35(5). 361–366. 15 indexed citations
16.
Veenendaal, A., et al.. (2003). Typing Single-Nucleotide Polymorphisms Using a Gel-Based Sequencer: A New Data Analysis Tool and Suggestions for Improved Efficiency. Molecular Biotechnology. 25(3). 283–288. 7 indexed citations
17.
Clausen, Peter‐Henning, et al.. (2003). Population genetic structure and cladistic analysis of Trypanosoma brucei isolates. Infection Genetics and Evolution. 3(3). 165–174. 6 indexed citations
18.
Pas, M.F.W. te, et al.. (2001). Regulation of selection-induced growth hormone expression in porcine single trait slection lines. Journal of Animal Science. 79. 30–30.
19.
Pas, M.F.W. te, E. J. Steenbergen, E.F. Knol, et al.. (2001). Associations between porcine leptin and leptin-receptor marker genotypes and immune parameters. Journal of Animal Science. 79. 189–189. 29 indexed citations
20.
Pas, M.F.W. te, et al.. (1994). Genetic regulation of meat production by embryonic muscle formation – a review. Journal of Animal Breeding and Genetics. 111(1-6). 404–412. 46 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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