Dominique Rocha

4.6k total citations
67 papers, 1.6k citations indexed

About

Dominique Rocha is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Dominique Rocha has authored 67 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Genetics, 31 papers in Molecular Biology and 13 papers in Cancer Research. Recurrent topics in Dominique Rocha's work include Genetic and phenotypic traits in livestock (34 papers), Genetic Mapping and Diversity in Plants and Animals (24 papers) and Cancer-related molecular mechanisms research (12 papers). Dominique Rocha is often cited by papers focused on Genetic and phenotypic traits in livestock (34 papers), Genetic Mapping and Diversity in Plants and Animals (24 papers) and Cancer-related molecular mechanisms research (12 papers). Dominique Rocha collaborates with scholars based in France, United Kingdom and Morocco. Dominique Rocha's co-authors include Mekki Boussaha, Bertrand Jordan, Didier Boichard, Christophe Klopp, Catherine Nguyen, Diane Esquerré, Samuel Granjeaud, Anis Djari, Sébastien Fritz and Philippe Naquet and has published in prestigious journals such as Nature Communications, PLoS ONE and Nature Reviews Genetics.

In The Last Decade

Dominique Rocha

64 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dominique Rocha France 22 955 637 347 229 202 67 1.6k
Krzysztof Flisikowski Germany 23 1.1k 1.1× 729 1.1× 375 1.1× 197 0.9× 153 0.8× 94 1.8k
Akiko Takasuga Japan 19 1.2k 1.2× 730 1.1× 441 1.3× 172 0.8× 139 0.7× 39 1.9k
Alex Van Zeveren Belgium 22 712 0.7× 810 1.3× 174 0.5× 242 1.1× 191 0.9× 92 1.8k
Gwenola Tosser‐Klopp France 27 1.3k 1.4× 609 1.0× 370 1.1× 196 0.9× 413 2.0× 58 2.0k
Jonathan E. Beever United States 25 1.2k 1.2× 705 1.1× 213 0.6× 156 0.7× 165 0.8× 86 2.0k
Mehmet Ulaş Çınar Türkiye 22 480 0.5× 493 0.8× 184 0.5× 250 1.1× 157 0.8× 96 1.3k
Minggang Lei China 21 499 0.5× 851 1.3× 444 1.3× 281 1.2× 88 0.4× 94 1.5k
Yulian Mu China 19 455 0.5× 828 1.3× 358 1.0× 132 0.6× 60 0.3× 82 1.3k
Christine Wurmser Germany 17 507 0.5× 359 0.6× 273 0.8× 79 0.3× 116 0.6× 34 943
Jakob Hedegaard Denmark 23 417 0.4× 1.0k 1.6× 510 1.5× 156 0.7× 49 0.2× 43 1.8k

Countries citing papers authored by Dominique Rocha

Since Specialization
Citations

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

Fields of papers citing papers by Dominique Rocha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dominique Rocha

This figure shows the co-authorship network connecting the top 25 collaborators of Dominique Rocha. A scholar is included among the top collaborators of Dominique Rocha 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 Dominique Rocha. Dominique Rocha 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
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Mariadassou, Mahendra, et al.. (2020). Detection of selection signatures in Limousin cattle using whole‐genome resequencing. Animal Genetics. 51(5). 815–819. 10 indexed citations
4.
Rebours, Emmanuelle, et al.. (2020). Survey of mitochondrial sequences integrated into the bovine nuclear genome. Scientific Reports. 10(1). 2077–2077. 17 indexed citations
5.
Boichard, Didier, Mekki Boussaha, Aurélien Capitan, et al.. (2018). Experience from large scale use of the EuroGenomics custom SNP chip in cattle. Prodinra (INRA Bordeaux-Aquitaine). 23 indexed citations
6.
Sanchez, Marie-Pierre, Armelle Govignon-Gion, Pascal Croiseau, et al.. (2017). Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle. Genetics Selection Evolution. 49(1). 68–68. 102 indexed citations
7.
Philippe, Romain, et al.. (2014). An integrative method to normalize RNA-Seq data. BMC Bioinformatics. 15(1). 188–188. 17 indexed citations
8.
Berg, Irene van den, Sébastien Fritz, Sabrina Rodriguez, et al.. (2014). Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology. Genetics Selection Evolution. 46(1). 31–31. 11 indexed citations
9.
Lejard, Véronique, et al.. (2014). Construction and validation of a novel dual reporter vector for studying mammalian bidirectional promoters. Plasmid. 74. 1–8. 6 indexed citations
10.
Lejard, Véronique, Emmanuelle Rebours, Mekki Boussaha, et al.. (2013). Bovine TWINKLE and mitochondrial ribosomal protein L43 genes are regulated by an evolutionary conserved bidirectional promoter. Gene. 537(1). 154–163. 5 indexed citations
11.
Fritz, Sébastien, Aurélien Capitan, Anis Djari, et al.. (2013). Detection of Haplotypes Associated with Prenatal Death in Dairy Cattle and Identification of Deleterious Mutations in GART, SHBG and SLC37A2. PLoS ONE. 8(6). e65550–e65550. 143 indexed citations
12.
Djari, Anis, Diane Esquerré, Bernard Weiss, et al.. (2013). Gene-based single nucleotide polymorphism discovery in bovine muscle using next-generation transcriptomic sequencing. BMC Genomics. 14(1). 307–307. 27 indexed citations
13.
Amigues, Yves, et al.. (2009). Genetic Variability and Linkage Disequilibrium Patterns in the Bovine DNAJA1 Gene. Molecular Biotechnology. 44(3). 190–197. 43 indexed citations
14.
Kwasiborski, Anthony, Dominique Rocha, & Claudia Terlouw. (2009). Gene expression in Large White or Duroc‐sired female and castrated male pigs and relationships with pork quality. Animal Genetics. 40(6). 852–862. 12 indexed citations
15.
Kwasiborski, Anthony, Thierry Sayd, Christophe Chambon, et al.. (2008). Pig Longissimus lumborum proteome: Part II: Relationships between protein content and meat quality. Meat Science. 80(4). 982–996. 63 indexed citations
16.
Ramos, A. M., et al.. (2006). Mapping of 21 genetic markers to a QTL region for meat quality on pig chromosome 17. Animal Genetics. 37(3). 296–297. 11 indexed citations
17.
Rocha, Dominique, Marta Gut, Alec J. Jeffreys, et al.. (2006). Seventh international meeting on single nucleotide polymorphism and complex genome analysis: ‘ever bigger scans and an increasingly variable genome’. Human Genetics. 119(4). 451–456. 23 indexed citations
18.
Mégy, Karyn, et al.. (2005). Mapping of the porcine serine carboxypeptidase vitellogenic‐like gene (CPVL) to chromosome 18. Animal Genetics. 36(2). 160–161. 2 indexed citations
19.
Kollers, Sonja, Sarah Blott, & Dominique Rocha. (2005). Confirmation of the mapping of the porcine calumenin gene (CALU ) to chromosome 18. Animal Genetics. 36(2). 177–178. 2 indexed citations
20.
Rovere, Patrizia, Jeannine Trucy, Valérie S. Zimmermann, et al.. (1997). Differential mRNA Expression in Untreated and TNF-α Elicited Murine Dendritic Cells Precursors. Advances in experimental medicine and biology. 417. 467–473. 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.

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