Alencar Xavier

• Google scholar
• LinkedIn
• ORCID
• Purdue Website
• Old website - LINK
• e-mail: alenxav@gmail.com
• phone: (+1) 765 631 2572

Resumes

• Academic resume
• Descriptive resume

Packages, apps

• MET accuracy app
• bWGR: Bayesian Whole Genome Regression & modeling tools (Active)
• mas: Multivariate/Multipopulation Association Studies (Active)
• NAM: Nested Association Mapping & breeding tools
• SoyNAM: Soybean Nested Association Mapping dataset

Background material

• Lecture directory
• Presentation on YouTube
• Lecture on variance components - R code, estimate variances and metrics (Nice one)
• Lecture on R basics - Example of R base code, including function and plots
• Mixed models lecture - Basic background on models, predictions, and signal detection

Methods and reviews

• Megavariate methods to capture GxE (Nice one)
• Efficient implementation of multivariate methods (Nice one)
• Efficient computation of marker effects
• Technical nuances of machine learning in GS
• Statistical black boxes of plant breeding

Investigation papers

• Quantitative genetics of yield components in soybeans
• Genetic architecture of phenomic-enabled canopy coverage in soy
• Unsupervised learning to infer tradeoffs among quantitative traits
• Quantitative metrics from the USDA soybean germplasm collection
• Joint modeling of genetics and field variation
• Factors impacting long-term gains in breeding

Links to talks and lectures

• Trends of predictive breeding. ASTA 2023. LINK
• Machine learning-based breeding. ASA-CSSA-SSSA 2023. LINK
• Machine learning-based AI applied to breeding. Purdue 2023. LINK
• Leveraging correlated information under multivariate settings. UGA 2023. LINK
• Maize Yield Predictions: 2022 G2F prediction competition. MGC 2023. LINK
• Xavier, A. Leveraging correlated information under multivariate settings. Plant Science symposium, UIUC, 2022. LINK
• Xavier, A. Modeling white mold with more than genomics. SBW, 2022. LINK
• Xavier, A. Implementation and Validation of supervised methods in GS, 2021 ASA CSSA SSSA meetings. LINK
• Xavier, A. Efficient computation of multivariate ridge regression, 2021 ASA CSSA SSSA meetings. LINK
• Xavier, A. Technical Nuances of Machine Learning. Iowa State University, 2021. LINK
• Xavier, A. Overview on Plant Breeding Analytics (lecture), Purdue University, 2021. LINK
• Xavier, A. Technical Nuances of Machine Learning in Plant Breeding, Iowa State Symposium, 2021. VIDEO, SLIDES.
• ANSC595, Quantitative Genomics Applied to Breeding (1 lecture), Purdue University, Fall 2019. LINK
• Xavier, A. Good learners, faster learning. IMPG3, University of Sao Paulo, 2019. LINK
• Xavier, A., Brito, L., Rainey, KM. Mixed models applied to breeding. Purdue, 2019. LINK
• Xavier, A. Good learners, faster learning. PAG, 2019. LINK
• Xavier, A. and Morota, G. Short course in mixed models. UFV, 2018. LINK
• AGRY611, Quantitative Genetics (7 lectures), Purdue University, Fall 2017. LINK
• Xavier, A. Analytical Methods for Phenomics. Purdue Phenomic Workshop, 2017. LINK

Research Areas

• Field Breeding and Efficient Data Collection
• Genome-wide Association Studies and QTL mapping
• Genome-wide prediction and genomic selection
• Multivariate and single-step mixed linear models
• Indirect Selection, Genetic Correlations, Improvement of Heritability and Genetic Gains
• Phenomics and High-Throughput Technologies in Plant Breeding
• Spatial Statistics, Adjustment of Field Variation and Imputation Methods
• Machine Learning, Data Mining, Computational Breeding, MCMC and Bayesian Analysis
• Algorithm development and high-performance computing
• Reaction norms for genotype-by-environment interaction modeling and stability
• Signatures of Selection and Applied Population Genetics