Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
20015.4k citationsBen J. Hayes, Michael E. Goddard et al.profile →
GCTA: A Tool for Genome-wide Complex Trait Analysis
20104.6k citationsMichael E. Goddard, Peter M. Visscher et al.profile →
Common SNPs explain a large proportion of the heritability for human height
20102.8k citationsMichael E. Goddard, Peter M. Visscher et al.Nature Geneticsprofile →
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
20161.6k citationsMichael E. Goddard, Naomi R. Wray et al.Nature Geneticsprofile →
Invited review: Genomic selection in dairy cattle: Progress and challenges
20091.3k citationsBen J. Hayes, P.J. Bowman et al.Journal of Dairy Scienceprofile →
Genomic selection: prediction of accuracy and maximisation of long term response
Countries citing papers authored by Michael E. Goddard
Since
Specialization
Citations
This map shows the geographic impact of Michael E. Goddard'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 E. Goddard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael E. Goddard more than expected).
Fields of papers citing papers by Michael E. Goddard
This network shows the impact of papers produced by Michael E. Goddard. 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 E. Goddard. The network helps show where Michael E. Goddard may publish in the future.
Co-authorship network of co-authors of Michael E. Goddard
This figure shows the co-authorship network connecting the top 25 collaborators of Michael E. Goddard.
A scholar is included among the top collaborators of Michael E. Goddard 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 E. Goddard. Michael E. Goddard is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Goddard, Michael E., Iona M. MacLeod, Kathryn E. Kemper, et al.. (2018). The use of multi-breed reference populations and multi-omic data to maximize accuracy of genomic prediction. Queensland's institutional digital repository (The University of Queensland). 115.2 indexed citations
9.
Liu, Zengting & Michael E. Goddard. (2018). A SNP MACE model for international genomic evaluation: technical challenges and possible solutions. Proceedings of the World Congress on Genetics Applied to Livestock Production. 393.
Erbe, Malena, et al.. (2014). Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels (vol 95, pg 4114, 2012). Journal of Dairy Science. 97(10).1 indexed citations
13.
Jagt, Christy Vander, et al.. (2014). A Gene Expression Atlas From Bovine RNAseq Data. Proceedings of the World Congress on Genetics Applied to Livestock Production. 180.3 indexed citations
Goddard, Michael E., et al.. (2003). Relationships between calving traits in heifers and mature cows in Australia. Bulletin - International Bull Evaluation Service/Interbull bulletin. 102.14 indexed citations
Goddard, Michael E.. (2001). Genetics to improve milk quality. Australian Journal of Dairy Technology. 56(2). 166–170.5 indexed citations
19.
Goddard, Michael E.. (1998). Advances in dairy cattle breeding research. Bulletin - International Bull Evaluation Service/Interbull bulletin. 37.5 indexed citations
20.
Wiggans, G.R. & Michael E. Goddard. (1996). A computationally feasible test day model with separate first and later lactation genetic effects. Bulletin - International Bull Evaluation Service/Interbull bulletin. 118.10 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.