A. E. Beattie

1.9k total citations · 1 hit paper
17 papers, 1.4k citations indexed

About

A. E. Beattie is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, A. E. Beattie has authored 17 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Genetics, 9 papers in Molecular Biology and 4 papers in Cancer Research. Recurrent topics in A. E. Beattie's work include Genetic and phenotypic traits in livestock (9 papers), Genetic Mapping and Diversity in Plants and Animals (6 papers) and Prion Diseases and Protein Misfolding (3 papers). A. E. Beattie is often cited by papers focused on Genetic and phenotypic traits in livestock (9 papers), Genetic Mapping and Diversity in Plants and Animals (6 papers) and Prion Diseases and Protein Misfolding (3 papers). A. E. Beattie collaborates with scholars based in New Zealand, Spain and France. A. E. Beattie's co-authors include K. G. Dodds, Grant W. Montgomery, Susan Galloway, Jennifer L. Juengel, Olli Ritvos, Mika Laitinen, Lisa Cambridge, G. H. Davis, T. Sakari Jokiranta and Kaisu Luiro and has published in prestigious journals such as Nature Genetics, Genetics and Bone.

In The Last Decade

A. E. Beattie

17 papers receiving 1.4k citations

Hit Papers

Mutations in an oocyte-derived growth factor gene (BMP15)... 2000 2026 2008 2017 2000 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. E. Beattie New Zealand 11 829 748 581 222 186 17 1.4k
Maurício Machaim Franco Brazil 19 565 0.7× 769 1.0× 531 0.9× 375 1.7× 220 1.2× 85 1.3k
B. Avery United Kingdom 26 858 1.0× 1.4k 1.9× 790 1.4× 563 2.5× 301 1.6× 82 1.9k
J. Folch Spain 17 415 0.5× 557 0.7× 236 0.4× 314 1.4× 327 1.8× 37 969
Marcelo Bertolini Brazil 20 458 0.6× 899 1.2× 575 1.0× 277 1.2× 354 1.9× 103 1.4k
R. S. Manik India 20 610 0.7× 973 1.3× 652 1.1× 418 1.9× 340 1.8× 110 1.4k
P. Palta India 19 538 0.6× 808 1.1× 596 1.0× 327 1.5× 305 1.6× 100 1.2k
Charles R. Long United States 25 1.0k 1.3× 1.2k 1.7× 1.5k 2.5× 761 3.4× 172 0.9× 61 2.5k
J. N. Caamaño Spain 25 429 0.5× 1.0k 1.4× 606 1.0× 624 2.8× 342 1.8× 65 1.5k
D. J. Tisdall New Zealand 17 306 0.4× 647 0.9× 368 0.6× 275 1.2× 322 1.7× 30 1.0k
Edmond Cribiu France 23 1.4k 1.7× 354 0.5× 756 1.3× 224 1.0× 160 0.9× 58 1.8k

Countries citing papers authored by A. E. Beattie

Since Specialization
Citations

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

Fields of papers citing papers by A. E. Beattie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. E. Beattie

This figure shows the co-authorship network connecting the top 25 collaborators of A. E. Beattie. A scholar is included among the top collaborators of A. E. Beattie 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 A. E. Beattie. A. E. Beattie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Phua, S. H., K. G. Dodds, C. A. Morris, et al.. (2008). A genome‐screen experiment to detect quantitative trait loci affecting resistance to facial eczema disease in sheep. Animal Genetics. 40(1). 73–79. 11 indexed citations
2.
Calvo, J. H., Carmen González, Carmen J. Serrano, et al.. (2008). Structural and functional analysis of the ovine laminin receptor gene (RPSA): Possible involvement of the LRP/LR protein in scrapie response. Mammalian Genome. 19(2). 92–105. 6 indexed citations
3.
Calvo, J. H., Carmen González, Katayoun Moazami‐Goudarzi, et al.. (2008). Structural and functional analysis of the HSP90AA1 gene: distribution of polymorphisms among sheep with different responses to scrapie. Cell Stress and Chaperones. 13(1). 19–29. 16 indexed citations
4.
Calvo, J. H., Carmen González, Katayoun Moazami‐Goudarzi, et al.. (2007). IL-1 family members as candidate genes modulating scrapie susceptibility in sheep: localization, partial characterization, and expression. Mammalian Genome. 18(1). 53–63. 10 indexed citations
5.
Calvo, J. H., et al.. (2006). Fine mapping of genes on sheep chromosome 1 and their association with milk traits. Animal Genetics. 37(3). 205–210. 13 indexed citations
6.
Crawford, Allan M., Korena A. Paterson, K. G. Dodds, et al.. (2006). Discovery of quantitative trait loci for resistance to parasitic nematode infection in sheep: I. Analysis of outcross pedigrees. BMC Genomics. 7(1). 178–178. 73 indexed citations
7.
Lyahyai, Jaber, Tom Goldammer, A. E. Beattie, P. Zaragoza, & Inmaculada Martín‐Burriel. (2005). Positional and functional characterisation of apoptosis related genes belonging to the BCL2 family in sheep. Cytogenetic and Genome Research. 109(4). 519–526. 4 indexed citations
8.
Calvo, J. H., et al.. (2004). Linkage mapping of ovine cysteine and histidine‐rich protein gene (CYHR1) to chromosome 9. Animal Genetics. 35(3). 263–264. 1 indexed citations
9.
Calvo, J. H., et al.. (2004). Ovine alpha‐amylase genes: isolation, linkage mapping and association analysis with milk traits. Animal Genetics. 35(4). 329–332. 10 indexed citations
10.
Campbell, A. W., W. E. Bain, Allan F. McRae, et al.. (2003). Bone density in sheep: genetic variation and quantitative trait loci localisation. Bone. 33(4). 540–548. 34 indexed citations
11.
Calvo, J. H., Daniel Vaiman, Nadhira Saïdi‐Mehtar, et al.. (2002). Characterization, genetic variation and chromosomal assignment to sheep chromosome 2 of the ovine heart fatty acid-binding protein gene (FABP3). Cytogenetic and Genome Research. 98(4). 270–273. 7 indexed citations
12.
Bodensteiner, Karin J., et al.. (2002). Genetic mapping of ovine growth differentiation factor 9 (GDF9) to sheep chromosome 5. Animal Genetics. 33(3). 244–245. 41 indexed citations
13.
Campbell, A. W., W. E. Bain, Allan F. McRae, et al.. (2002). DETECTION OF QUANTITATIVE TRAIT LOCI FOR BONE MINERAL DENSITY IN COOPWORTH SHEEP. 0–4. 1 indexed citations
14.
Galloway, Susan, Kenneth P. McNatty, Lisa Cambridge, et al.. (2000). Mutations in an oocyte-derived growth factor gene (BMP15) cause increased ovulation rate and infertility in a dosage-sensitive manner. Nature Genetics. 25(3). 279–283. 864 indexed citations breakdown →
15.
Walling, G.A., K. G. Dodds, Susan Galloway, et al.. (2000). The consequences of carrying the Booroola fecundity (FecB) gene on sheep liveweight. Proceedings of the British Society of Animal Science. 2000. 43–43. 4 indexed citations
16.
Montgomery, Grant W., Hannah Henry, K. G. Dodds, et al.. (1996). Mapping the Horns (Ho) Locus in Sheep: A Further Locus Controlling Horn Development in Domestic Animals. Journal of Heredity. 87(5). 358–363. 36 indexed citations
17.
Crawford, A. M., K. G. Dodds, A J Ede, et al.. (1995). An autosomal genetic linkage map of the sheep genome.. Genetics. 140(2). 703–724. 304 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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