D. J. Brown

3.2k total citations
178 papers, 2.3k citations indexed

About

D. J. Brown is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, D. J. Brown has authored 178 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Genetics, 40 papers in Agronomy and Crop Science and 38 papers in Animal Science and Zoology. Recurrent topics in D. J. Brown's work include Genetic and phenotypic traits in livestock (111 papers), Genetic Mapping and Diversity in Plants and Animals (31 papers) and Effects of Environmental Stressors on Livestock (28 papers). D. J. Brown is often cited by papers focused on Genetic and phenotypic traits in livestock (111 papers), Genetic Mapping and Diversity in Plants and Animals (31 papers) and Effects of Environmental Stressors on Livestock (28 papers). D. J. Brown collaborates with scholars based in Australia, United States and Norway. D. J. Brown's co-authors include Andrew Swan, Abe Huisman, J. H. J. van der Werf, Robert E. Harmon, S. K. Gupta, Robert Banks, Geoffrey Hinch, N. M. Fogarty, Alex J. Ball and Darryl Savage and has published in prestigious journals such as Nature, Science and Chemical Reviews.

In The Last Decade

D. J. Brown

170 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. J. Brown Australia 28 1.1k 573 501 409 318 178 2.3k
Bjarne Nielsen Denmark 22 859 0.8× 293 0.5× 141 0.3× 451 1.1× 205 0.6× 89 2.1k
Yachun Wang China 31 1.5k 1.3× 1.0k 1.8× 944 1.9× 321 0.8× 664 2.1× 228 3.3k
Masashi Takahashi Japan 27 528 0.5× 407 0.7× 606 1.2× 70 0.2× 924 2.9× 144 2.9k
Lawrence B. Schook United States 44 2.6k 2.3× 628 1.1× 340 0.7× 235 0.6× 2.3k 7.3× 230 6.4k
Rong Hou China 27 556 0.5× 188 0.3× 80 0.2× 116 0.3× 1.3k 4.0× 267 3.1k
Jeffrey E. Plowman New Zealand 27 215 0.2× 198 0.3× 68 0.1× 42 0.1× 743 2.3× 93 2.2k
Joël Gautron France 37 603 0.5× 1.9k 3.3× 83 0.2× 83 0.2× 841 2.6× 84 4.1k
Alexandre Rodrigues Silva Brazil 25 487 0.4× 334 0.6× 205 0.4× 170 0.4× 299 0.9× 237 2.4k
Xiquan Zhang China 43 1.3k 1.2× 1.2k 2.1× 165 0.3× 45 0.1× 2.7k 8.3× 289 5.6k
Colin J. Wilde United Kingdom 31 757 0.7× 279 0.5× 570 1.1× 128 0.3× 776 2.4× 81 2.6k

Countries citing papers authored by D. J. Brown

Since Specialization
Citations

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

Fields of papers citing papers by D. J. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. J. Brown. 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 D. J. Brown. The network helps show where D. J. Brown may publish in the future.

Co-authorship network of co-authors of D. J. Brown

This figure shows the co-authorship network connecting the top 25 collaborators of D. J. Brown. A scholar is included among the top collaborators of D. J. Brown 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 D. J. Brown. D. J. Brown 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
2.
Bunter, K. L., et al.. (2023). The genetic and phenotypic associations between lamb survival outcomes and other traits recorded at lambing. Animal Production Science. 63(11). 1148–1159. 1 indexed citations
3.
Flitcroft, Rebecca, Michael R. Mulvey, Krista L. Jones, et al.. (2023). Science to support conservation action in a large river system: The Willamette River, Oregon, USA. SHILAP Revista de lepidopterología. 2(4). 100203–100203. 3 indexed citations
4.
Paganoni, B. L., Clifford L. W. Jones, D. J. Brown, et al.. (2023). Methane, growth and carcase considerations when breeding for more efficient Merino sheep production. animal. 17(11). 100999–100999.
5.
Notter, D. R., et al.. (2022). Model definition for genetic evaluation of purebred and crossbred lambs including heterosis. Journal of Animal Science. 100(6). 7 indexed citations
6.
Li, Li, et al.. (2021). Single-step genomic evaluation of lambing ease in Australian terminal sire breed sheep. Animal Production Science. 61(18). 1990–1999. 4 indexed citations
7.
Swan, Andrew, et al.. (2018). Cross-validation of single step BLUP applied to terminal sire sheep in Australia. RUNE (Research UNE). 362. 3 indexed citations
8.
Brown, D. J., Andrew Swan, Li Li, et al.. (2018). Single-Step Genetic Evaluations in the Australian Sheep Industry. RUNE (Research UNE). 460. 10 indexed citations
9.
Brown, D. J., et al.. (2018). A decade of sheep genetics: what have we achieved?. RUNE (Research UNE). 661. 3 indexed citations
10.
Brown, D. J., et al.. (2016). Evaluating the effects of feral deer management on endangered alpine peatlands: The Alpine National Park deer control trial. Plant protection quarterly. 31(2). 63. 3 indexed citations
11.
Brown, D. J., Alex J. Ball, Abe Huisman, et al.. (2006). Sheep Genetics Australia: a national genetic evaluation system for Australian sheep.. RUNE (Research UNE). 13 indexed citations
12.
Huisman, Abe & D. J. Brown. (2006). Predictive ability of sire weaning weight breeding values estimated across environments in terminal sire sheep breeds. RUNE (Research UNE). 4–7. 1 indexed citations
13.
Brown, D. J., et al.. (2003). Preliminary genetic parameters for live weight and ultrasound scan traits in Merinos. RUNE (Research UNE). 9 indexed citations
14.
Brown, D. J., et al.. (2002). Incorporating subjectively assessed sheep and wool traits into genetic evaluations for Merino sheep. 2: Phenotypic and genetic correlations. Wool technology and sheep breeding. 50(3). 378–382. 12 indexed citations
15.
Brown, D. J., et al.. (2002). Incorporating subjectively assessed sheep and wool traits into genetic evaluations for Merino sheep. 1: Phenotypic variation and heritabilities.. Wool technology and sheep breeding. 50(3). 373–377. 5 indexed citations
16.
Brown, D. J. & A. C. Schlink. (2002). A comparison of fibre diameter profiles generated using 2 mm snippet techniques to those measured using the OFDA2000.. Wool technology and sheep breeding. 50(1). 27–39. 2 indexed citations
17.
Brown, D. J., Bruce Tier, Antônio Reverter, Robert Banks, & H. U. Graser. (2000). OVIS: a multiple trait breeding value estimation program for genetic evaluation of sheep.. Wool technology and sheep breeding. 48(4). 285–297. 29 indexed citations
18.
Brown, D. J., et al.. (2000). The measurement of skin thickness in Merino sheep using real time ultrasound.. Wool technology and sheep breeding. 48(4). 269–276. 12 indexed citations
19.
Brown, D. J., et al.. (2000). Variation in fibre diameter profile characteristics between wool staples in Merino sheep.. Wool technology and sheep breeding. 48(2). 86–93. 5 indexed citations
20.
Ludwig, Jens, et al.. (1997). Does r-EAG contribute to the M-current?. UCL Discovery (University College London). 6 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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