Michael T. Rose

1.9k total citations
83 papers, 1.3k citations indexed

About

Michael T. Rose is a scholar working on Molecular Biology, Agronomy and Crop Science and Genetics. According to data from OpenAlex, Michael T. Rose has authored 83 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 27 papers in Agronomy and Crop Science and 19 papers in Genetics. Recurrent topics in Michael T. Rose's work include Reproductive Physiology in Livestock (16 papers), Genetic and phenotypic traits in livestock (12 papers) and Effects of Environmental Stressors on Livestock (11 papers). Michael T. Rose is often cited by papers focused on Reproductive Physiology in Livestock (16 papers), Genetic and phenotypic traits in livestock (12 papers) and Effects of Environmental Stressors on Livestock (11 papers). Michael T. Rose collaborates with scholars based in United Kingdom, Japan and United States. Michael T. Rose's co-authors include Hisashi Aso, Y. Obara, Kouichi Watanabe, Fumiaki Itoh, Shyuichi Ohwada, Hitoshi Watanabe, Takashi Kanaya, Takahiro Yamaguchi, Haruki Kitazawa and Ikuro Takakura and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and PLoS ONE.

In The Last Decade

Michael T. Rose

79 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael T. Rose United Kingdom 21 388 285 264 221 210 83 1.3k
Pietro Lombardi Italy 25 413 1.1× 338 1.2× 277 1.0× 146 0.7× 379 1.8× 136 2.4k
L. Martin France 12 503 1.3× 281 1.0× 122 0.5× 285 1.3× 130 0.6× 20 1.4k
Daniel Clark United States 24 336 0.9× 670 2.4× 229 0.9× 146 0.7× 166 0.8× 96 1.5k
M. Mielenz Germany 23 283 0.7× 338 1.2× 710 2.7× 278 1.3× 308 1.5× 61 1.6k
Myriam Hesta Belgium 24 533 1.4× 404 1.4× 188 0.7× 367 1.7× 226 1.1× 134 1.9k
Jarosław Woliński Poland 18 192 0.5× 257 0.9× 129 0.5× 180 0.8× 117 0.6× 83 1.2k
Neil E. Forsberg United States 15 464 1.2× 250 0.9× 182 0.7× 162 0.7× 84 0.4× 29 1.1k
Mihir Sarkar India 28 652 1.7× 700 2.5× 650 2.5× 214 1.0× 490 2.3× 130 2.0k
Udaya DeSilva United States 22 710 1.8× 342 1.2× 762 2.9× 199 0.9× 424 2.0× 57 2.2k
Walter T. Dixon Canada 26 711 1.8× 552 1.9× 391 1.5× 283 1.3× 444 2.1× 81 2.3k

Countries citing papers authored by Michael T. Rose

Since Specialization
Citations

This map shows the geographic impact of Michael T. Rose'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 Michael T. Rose with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael T. Rose more than expected).

Fields of papers citing papers by Michael T. Rose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael T. Rose. 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 Michael T. Rose. The network helps show where Michael T. Rose may publish in the future.

Co-authorship network of co-authors of Michael T. Rose

This figure shows the co-authorship network connecting the top 25 collaborators of Michael T. Rose. A scholar is included among the top collaborators of Michael T. Rose 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 Michael T. Rose. Michael T. Rose 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.
2.
Sato, Hidetoshi, Tomohito Hayashi, Yuya Nagasawa, et al.. (2024). Elevated levels of cyclophilin A secreted in milk during bovine mastitis. Journal of Dairy Science. 108(1). 835–844.
3.
Bull, Michelle, et al.. (2023). Understanding the microbial fibre degrading communities & processes in the equine gut. SHILAP Revista de lepidopterología. 5(1). 19 indexed citations
4.
Rose, Michael T., et al.. (2019). In Vitro and In Vivo Activity of a Novel Antisense Peptide Nucleic Acid Compound Against Multidrug-Resistant Acinetobacter baumannii. Microbial Drug Resistance. 25(7). 961–965. 11 indexed citations
5.
6.
King, Jonathan M., Toby Wilkinson, Hilary J. Worgan, et al.. (2017). Comparison of the microbial population in rabbits and guinea pigs by next generation sequencing. PLoS ONE. 12(2). e0165779–e0165779. 54 indexed citations
7.
Nochi, Tomonori, Katsuyoshi Sato, Tomohito Hayashi, et al.. (2015). Extracellular cyclophilin A possesses chemotaxic activity in cattle. Veterinary Research. 46(1). 80–80. 9 indexed citations
8.
Watanabe, Hitoshi, Ryo� Saito, Tatsuya Nakano, et al.. (2014). Effect of Peripheral 5-HT on Glucose and Lipid Metabolism in Wether Sheep. PLoS ONE. 9(2). e88058–e88058. 30 indexed citations
9.
Rose, Michael T.. (2012). Effect of growth factors on the migration of equine oral and limb fibroblasts using an in vitro scratch assay. The Veterinary Journal. 193(2). 539–544. 8 indexed citations
10.
Rose, Michael T., et al.. (2012). Effect of iodine, selenium and cobalt rumen boluses given to dry dairy cows on the immunoglobulin and thyroid hormone status of calves. Animal Science Journal. 83(7). 543–548. 7 indexed citations
11.
Takakura, Ikuro, Kohtaro Miyazawa, Takashi Kanaya, et al.. (2011). Orally Administered Prion Protein Is Incorporated by M Cells and Spreads into Lymphoid Tissues with Macrophages in Prion Protein Knockout Mice. American Journal Of Pathology. 179(3). 1301–1309. 36 indexed citations
12.
Watanabe, Hitoshi, Michael T. Rose, & Hisashi Aso. (2011). Role of peripheral serotonin in glucose and lipid metabolism. Current Opinion in Lipidology. 22(3). 186–191. 54 indexed citations
13.
Miyazawa, Kohtaro, Takashi Kanaya, Sachi Tanaka, et al.. (2009). Characterization of newly established bovine intestinal epithelial cell line. Histochemistry and Cell Biology. 133(1). 125–134. 61 indexed citations
14.
Nagai, Yasuhiro, Hisashi Aso, Hideki Ogasawara, et al.. (2008). Anterior Pituitary Progenitor Cells Express Costimulatory Molecule 4Ig-B7-H3. The Journal of Immunology. 181(9). 6073–6081. 9 indexed citations
15.
Rose, Michael T., et al.. (2006). The Long Road to a Representative In Vitro Model of Bovine Lactation. 3(3). 67–72. 6 indexed citations
16.
Kanaya, Takashi, Hisashi Aso, Kohtaro Miyazawa, et al.. (2006). Staining patterns for actin and villin distinguish M cells in bovine follicle-associated epithelium. Research in Veterinary Science. 82(2). 141–149. 15 indexed citations
17.
Aso, Hisashi, et al.. (2004). Cloning and expression of type XII collagen isoforms during bovine adipogenesis. Differentiation. 72(4). 113–122. 15 indexed citations
18.
Itoh, Fumiaki, et al.. (1998). Heat influences on plasma insulin and glucagon in response to secretogogues in non-lactating dairy cows. Domestic Animal Endocrinology. 15(6). 499–510. 20 indexed citations
19.
Rose, Michael T., Y. Obara, Fumiaki Itoh, H Hashimoto, & Yûji Takahashi. (1997). Growth hormone does not affect non‐insulin‐mediated glucose uptake in sheep. Experimental Physiology. 82(4). 749–760. 6 indexed citations
20.
Preti, Robert A., et al.. (1994). The Combined Use of Soybean Agglutinin and Immunomagnetic Beads for T Lymphocyte Subset Depletion of Bone Marrow Allografts: A Laboratory Analysis. Journal of Hematotherapy. 3(2). 111–120. 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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