María A. Raschia

497 total citations
23 papers, 333 citations indexed

About

María A. Raschia is a scholar working on Genetics, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, María A. Raschia has authored 23 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 7 papers in Surgery and 6 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in María A. Raschia's work include Genetic and phenotypic traits in livestock (9 papers), Pancreatic function and diabetes (7 papers) and Diet, Metabolism, and Disease (6 papers). María A. Raschia is often cited by papers focused on Genetic and phenotypic traits in livestock (9 papers), Pancreatic function and diabetes (7 papers) and Diet, Metabolism, and Disease (6 papers). María A. Raschia collaborates with scholars based in Argentina, Brazil and United States. María A. Raschia's co-authors include Juan José Gagliardino, Bárbara Maiztegui, Héctor Del Zotto, Flavio Francini, María Laura Massa, María I. Borelli, Mario Andrés Poli, Luis Flores, María Cecilia Castro and Ariel Amadío and has published in prestigious journals such as Archives of Biochemistry and Biophysics, Gene and Life Sciences.

In The Last Decade

María A. Raschia

22 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
María A. Raschia Argentina 10 178 94 88 87 80 23 333
Virginia M. Stone Sweden 13 120 0.7× 154 1.6× 130 1.5× 82 0.9× 133 1.7× 23 509
L. Belair France 9 147 0.8× 19 0.2× 96 1.1× 49 0.6× 98 1.2× 10 334
Cloyce L. Stetson United States 8 45 0.3× 31 0.3× 73 0.8× 46 0.5× 100 1.3× 31 338
H. Laube Germany 13 174 1.0× 115 1.2× 75 0.9× 46 0.5× 91 1.1× 34 394
Emmanuelle Martinot France 12 35 0.2× 82 0.9× 85 1.0× 37 0.4× 150 1.9× 18 400
S Araki Japan 13 87 0.5× 27 0.3× 38 0.4× 12 0.1× 110 1.4× 29 418
Xiaoming Hou China 14 35 0.2× 51 0.5× 174 2.0× 30 0.3× 292 3.6× 36 551
Sarah L. Giesy United States 13 40 0.2× 20 0.2× 59 0.7× 52 0.6× 158 2.0× 22 369
Jinhee Hwang South Korea 12 28 0.2× 20 0.2× 33 0.4× 41 0.5× 119 1.5× 36 332
V. Praveen Chakravarthi United States 12 34 0.2× 33 0.4× 113 1.3× 20 0.2× 152 1.9× 35 468

Countries citing papers authored by María A. Raschia

Since Specialization
Citations

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

Fields of papers citing papers by María A. Raschia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María A. Raschia. 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 María A. Raschia. The network helps show where María A. Raschia may publish in the future.

Co-authorship network of co-authors of María A. Raschia

This figure shows the co-authorship network connecting the top 25 collaborators of María A. Raschia. A scholar is included among the top collaborators of María A. Raschia 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 María A. Raschia. María A. Raschia 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.
Poli, Mario Andrés, et al.. (2023). Genetic resistance to gastrointestinal parasites in sheep. CABI Reviews.
2.
Raschia, María A., et al.. (2023). Modification of a previously patented method to unequivocally score A2-like and A1-like bovine β-casein variants. MethodsX. 10. 102183–102183. 1 indexed citations
3.
Raschia, María A., et al.. (2023). Quantitative trait loci exploration and characterization of gestation length in Holstein cattle. Theriogenology. 215. 43–49. 3 indexed citations
4.
Raschia, María A., et al.. (2022). Methodology for the identification of relevant loci for milk traits in dairy cattle, using machine learning algorithms. MethodsX. 9. 101733–101733. 1 indexed citations
5.
Raschia, María A., et al.. (2022). Deletion in KARLN intron 5 and predictive relationship with bovine tuberculosis and brucellosis infection phenotype. Veterinary Research Communications. 47(2). 779–789. 2 indexed citations
6.
7.
Raschia, María A., D.O. Maizon, Víctor Humberto Súarez, et al.. (2020). Single nucleotide polymorphisms from candidate genes associated with nematode resistance and resilience in Corriedale and Pampinta sheep in Argentina. Gene. 770. 145345–145345. 7 indexed citations
8.
Raschia, María A., Ariel Amadío, Gerónimo Gutiérrez, et al.. (2018). Genome-wide scan for commons SNPs affecting bovine leukemia virus infection level in dairy cattle. BMC Genomics. 19(1). 142–142. 24 indexed citations
9.
10.
Raschia, María A., et al.. (2018). Single nucleotide polymorphisms in candidate genes associated with milk yield in Argentinean Holstein and Holstein x Jersey cows. Journal of Animal Science and Technology. 60(1). 31–31. 20 indexed citations
11.
Raschia, María A., et al.. (2015). Single nucleotide polymorphisms in candidate genes and their relation with somatic cell scores in Argentinean dairy cattle. Journal of Applied Genetics. 56(4). 505–513. 6 indexed citations
12.
Raschia, María A., et al.. (2015). Genome-wide association study for somatic cell score in Argentinean dairy cattle. Livestock Science. 175. 1–9. 6 indexed citations
13.
Flores, Luis, et al.. (2014). Islet NADPH oxidase activity modulates β-cell mass and endocrine function in rats with fructose-induced oxidative stress. Biochimica et Biophysica Acta (BBA) - General Subjects. 1840(12). 3475–3482. 10 indexed citations
14.
Flores, Luis, et al.. (2013). Islet Cannabinoid Receptors. Pancreas. 42(7). 1085–1092. 13 indexed citations
15.
Francini, Flavio, María Cecilia Castro, Guillermo Schinella, et al.. (2010). Changes induced by a fructose-rich diet on hepatic metabolism and the antioxidant system. Life Sciences. 86(25-26). 965–971. 82 indexed citations
16.
Maiztegui, Bárbara, María I. Borelli, Héctor Del Zotto, et al.. (2010). Sitagliptin prevents the development of metabolic and hormonal disturbances, increased β-cell apoptosis and liver steatosis induced by a fructose-rich diet in normal rats. Clinical Science. 120(2). 73–80. 53 indexed citations
17.
Rebolledo, Oscar R., et al.. (2010). Islet NADPH oxidase activity is modulated unevenly by different secretagogues. Endocrine. 38(2). 309–311. 2 indexed citations
18.
Raschia, María A., et al.. (2009). Changes in islet plasma membrane calcium-ATPase activity and isoform expression induced by insulin resistance. Archives of Biochemistry and Biophysics. 490(1). 17–23. 9 indexed citations
19.
Zotto, Héctor Del, Bárbara Maiztegui, María A. Raschia, et al.. (2009). Islet neogenesis-associated protein pentadecapeptide (INGAP-PP): Mechanisms involved in its effect upon β-cell mass and function. Regulatory Peptides. 157(1-3). 25–31. 15 indexed citations
20.
Maiztegui, Bárbara, María I. Borelli, María A. Raschia, Héctor Del Zotto, & Juan José Gagliardino. (2008). Islet adaptive changes to fructose-induced insulin resistance: β-cell mass, glucokinase, glucose metabolism, and insulin secretion. Journal of Endocrinology. 200(2). 139–149. 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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