Emi Tanaka
Emi Tanaka
Lecturer in Statistics, Monash University
Verified email at monash.edu - Homepage
Cited by
Cited by
Improved similarity scores for comparing motifs
E Tanaka, T Bailey, CE Grant, WS Noble, U Keich
Bioinformatics 27 (12), 1603-1609, 2011
Novel features of ARS selection in budding yeast Lachancea kluyveri
I Liachko, E Tanaka, K Cox, SCC Chung, L Yang, A Seher, L Hallas, ...
BMC genomics 12 (1), 633, 2011
Improving MEME via a two-tiered significance analysis
E Tanaka, TL Bailey, U Keich
Bioinformatics 30 (14), 1965-1973, 2014
Increased genomic prediction accuracy in wheat breeding using a large Australian panel
A Norman, J Taylor, E Tanaka, P Telfer, J Edwards, JP Martinant, ...
Theoretical and applied genetics 130 (12), 2543-2555, 2017
Order selection and sparsity in latent variable models via the ordered factor LASSO
FKC Hui, E Tanaka, DI Warton
Biometrics 74 (4), 1311-1319, 2018
Increased accuracy of starch granule type quantification using mixture distributions
E Tanaka, JPF Ral, S Li, R Gaire, CR Cavanagh, BR Cullis, A Whan
Plant methods 13 (1), 107, 2017
Simple robust genomic prediction and outlier detection for a multi-environmental field trial
E Tanaka
arXiv preprint arXiv:1807.07268, 2018
Increased genomic prediction accuracy in wheat breeding using a large Australian panel
J Taylor, A Norman, E Tanaka, P Telfer, J Edwards, J Martinant, H Kuchel
Springer Verlag, 2017
Linkage map construction for the Cranbrook x Halberd mapping population
B Cullis, E Tanaka, L Borg, A Smith
Simple outlier detection for a multi‐environmental field trial
E Tanaka
Biometrics, 2020
Symbolic Formulae for Linear Mixed Models
E Tanaka, FKC Hui
Research School on Statistics and Data Science, 3-21, 2019
Clustered and dispersed chromosomal distribution of the two classes of Revolver transposon family in Secale cereale
M Tomita, T Kanzaki, E Tanaka
Linear mixed models for genomic selection
A Smith, E Tanaka, B Cullis, R Thompson
Statistical Protocols for Late Maturity alpha-amylase in Wheat
N Cocks, B Cullis, E Tanaka
Statistical Methods for Improving Motif Evaluation
E Tanaka
University of Sydney, 2014
Loss of accuracy in the genomic prediction for prevalent two-stage analysis with single site.
E Tanaka, K Mathews, AB Smith, BR Cullis
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