M. Silberberg

2.4k total citations
73 papers, 1.6k citations indexed

About

M. Silberberg is a scholar working on Genetics, Agronomy and Crop Science and Rheumatology. According to data from OpenAlex, M. Silberberg has authored 73 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Genetics, 17 papers in Agronomy and Crop Science and 12 papers in Rheumatology. Recurrent topics in M. Silberberg's work include Ruminant Nutrition and Digestive Physiology (17 papers), Genetic and phenotypic traits in livestock (9 papers) and Reproductive Physiology in Livestock (9 papers). M. Silberberg is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (17 papers), Genetic and phenotypic traits in livestock (9 papers) and Reproductive Physiology in Livestock (9 papers). M. Silberberg collaborates with scholars based in France, United States and Morocco. M. Silberberg's co-authors include Ruth Silberberg, Cécile Martin, Diego Morgavi, Christine Morand, Augustin Scalbert, Christian Rémésy, Isabelle Veissier, Claudine Manach, Pierre Nozière and Abderzak Lettat and has published in prestigious journals such as Journal of Biological Chemistry, Applied and Environmental Microbiology and Journal of Agricultural and Food Chemistry.

In The Last Decade

M. Silberberg

66 papers receiving 1.5k 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. Silberberg France 21 462 293 213 197 197 73 1.6k
P. E. V. Williams United States 22 502 1.1× 363 1.2× 474 2.2× 63 0.3× 252 1.3× 77 2.1k
Marie‐France Palin Canada 30 798 1.7× 641 2.2× 532 2.5× 135 0.7× 543 2.8× 112 3.1k
H.D. Eaton United States 18 164 0.4× 255 0.9× 301 1.4× 55 0.3× 78 0.4× 99 1.0k
Yanli Liu China 28 122 0.3× 910 3.1× 520 2.4× 168 0.9× 171 0.9× 163 2.5k
Junhu Yao China 28 813 1.8× 654 2.2× 587 2.8× 47 0.2× 314 1.6× 121 2.2k
Ibrahim Marai Israel 24 577 1.2× 132 0.5× 1.7k 7.8× 163 0.8× 375 1.9× 91 2.8k
Haijun Gao China 24 535 1.2× 847 2.9× 161 0.8× 35 0.2× 286 1.5× 58 2.4k
G.H. McIntosh Australia 21 87 0.2× 306 1.0× 110 0.5× 17 0.1× 153 0.8× 66 1.8k
Yoo Yong Kim South Korea 21 89 0.2× 175 0.6× 453 2.1× 134 0.7× 172 0.9× 75 1.4k
Shawn S. Donkin United States 36 1.7k 3.7× 740 2.5× 702 3.3× 72 0.4× 902 4.6× 134 4.2k

Countries citing papers authored by M. Silberberg

Since Specialization
Citations

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

Fields of papers citing papers by M. Silberberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Silberberg

This figure shows the co-authorship network connecting the top 25 collaborators of M. Silberberg. A scholar is included among the top collaborators of M. Silberberg 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. Silberberg. M. Silberberg 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.
Dunière, Lysiane, Philippe Ruiz, Frédérique Chaucheyras‐Durand, et al.. (2025). Evaluation of esophageal tubing and buccal swabbing versus rumen cannula to characterize ruminal microbiota in cows fed contrasting diets. Scientific Reports. 15(1). 34582–34582.
2.
3.
Coppa, Mauro, Clothilde Villot, Cécile Martin, & M. Silberberg. (2023). On-farm evaluation of multiparametric models to predict subacute ruminal acidosis in dairy cows. animal. 17(6). 100826–100826. 2 indexed citations
4.
Mialon, Marie‐Madeleine, Karen Helle Sloth, Romain Lardy, et al.. (2020). Detection of changes in the circadian rhythm of cattle in relation to disease, stress, and reproductive events. Methods. 186. 14–21. 29 indexed citations
5.
Villot, Clothilde, Cécile Martin, D. Durand, et al.. (2019). Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge. animal. 14(2). 388–398. 8 indexed citations
6.
Philippeau, Christelle, Abderzak Lettat, Cécile Martin, et al.. (2017). Effects of bacterial direct-fed microbials on ruminal characteristics, methane emission, and milk fatty acid composition in cows fed high- or low-starch diets. Journal of Dairy Science. 100(4). 2637–2650. 51 indexed citations
7.
Villot, Clothilde, et al.. (2017). Relative reticulo-rumen pH indicators for subacute ruminal acidosis detection in dairy cows. animal. 12(3). 481–490. 53 indexed citations
8.
Morgavi, Diego, M. Silberberg, Frédérique Chaucheyras‐Durand, et al.. (2016). Bioavailability of aflatoxin B1 and ochratoxin A, but not fumonisin B1 or deoxynivalenol, is increased in starch-induced low ruminal pH in nonlactating dairy cows. Journal of Dairy Science. 99(12). 9759–9767. 15 indexed citations
9.
Nozière, Pierre, Christian E. W. Steinberg, M. Silberberg, & Diego Morgavi. (2014). Amylase addition increases starch ruminal digestion in first-lactation cows fed high and low starch diets. Journal of Dairy Science. 97(4). 2319–2328. 58 indexed citations
10.
Silberberg, M., Frédérique Chaucheyras‐Durand, Marie‐Madeleine Mialon, et al.. (2013). Repeated acidosis challenges and live yeast supplementation shape rumen microbiota and fermentations and modulate inflammatory status in sheep. animal. 7(12). 1910–1920. 41 indexed citations
11.
12.
Silberberg, M., et al.. (2012). Behavioural adaptations of sheep to repeated acidosis challenges and effect of yeast supplementation. animal. 6(12). 2011–2022. 15 indexed citations
13.
Silberberg, M., Ángel Gil‐Izquierdo, Lydie Combaret, et al.. (2006). Flavanone metabolism in healthy and tumor-bearing rats. Biomedicine & Pharmacotherapy. 60(9). 529–535. 61 indexed citations
14.
Silberberg, M., Christine Morand, Claudine Manach, Augustin Scalbert, & Christian Rémésy. (2005). Co-administration of quercetin and catechin in rats alters their absorption but not their metabolism. Life Sciences. 77(25). 3156–3167. 49 indexed citations
15.
Silberberg, Ruth & M. Silberberg. (2003). Degenerative joint disease in ovariectomized mice fed a high-fat diet.. PubMed. 3(3). 228–39.
16.
Couplan, Elodie, C. Gelly, Marc Goubern, et al.. (2002). High Level of Uncoupling Protein 1 Expression in Muscle of Transgenic Mice Selectively Affects Muscles at Rest and Decreases Their IIb Fiber Content. Journal of Biological Chemistry. 277(45). 43079–43088. 54 indexed citations
17.
Silberberg, M., Ruth Silberberg, & Mary Hasler. (1966). Fine structure of articular cartilage in mice receiving cortisone acetate.. Medical Entomology and Zoology. 82(6). 569–82. 44 indexed citations
18.
Silberberg, M. & Ruth Silberberg. (1963). Role of sex hormone in the pathogenesis of osteoarthrosis of mice.. The Mouseion at the JAXlibrary (Jackson Laboratory). 12. 285–9. 28 indexed citations
19.
Silberberg, Ruth, et al.. (1962). Effects of Diet during Growth. Pathobiology. 25(1). 56–66. 23 indexed citations
20.
Silberberg, M.. (1960). Die Altersveranderungen Der Halswirbelsaule. Journal of Gerontology. 15(4). 400–400. 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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