M. Malosetti
Plant Science · 2004–2016
A researcher in the Science corpus: 5 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Plant Science — 65 citations into it; #7,802 of 8,232 by trust here, #4,762 by citations
- Genetics — 52 citations into it; #6,516 of 6,854 by trust here, #3,435 by citations
- Statistics and Probability — 8 citations into it
Whom M. Malosetti trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geert Verbeke
- Yoav Benjamini
- J. Li
- Scott C. Chapman
- Graeme L. Hammer
- Geert Molenberghs
- Y. Hochberg
- L. Ji
- Mark Cooper
- Jose Crossa
Who trusts M. Malosetti overall
Papers from M. Malosetti's perspective
Ordered by how strongly the researchers M. Malosetti trusts endorse each paper. Same corpus, a different order for every researcher.
- Controlling the false discovery rate: a practical and powerful approach to multiple testing
- Linear Mixed Models for Longitudinal Data (Technometrics)
- Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments
- Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects (Agronomy Journal)
- Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix (Heredity)
- Genetics and Analysis of Quantitative Traits.
- Gene-to-phenotype models and complex trait genetics
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
- Statistical Analysis With Missing Data
- Statistical significance for genomewide studies (Proceedings of the National Academy of Sciences of the United States of America)
Their papers
- What should students in plant breeding know about the statistical aspects of genotype × Environment interactions? (2016) — 244 citations
- Predicting responses in multiple environments : Issues in relation to genotype × Environment interactions (2016) — 92 citations
- A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.) (2008) — 164 citations
- Statistical models for genotype by environment data: from conventional ANOVA models to eco-physiological QTL models (2005) — 127 citations
- Mixed models including environmental covariables for studying QTL by environment interaction (2004) — 157 citations